\r\n\t \r\n\tThe aims of this book are to present the updates and advances in the field of resuscitation including AHA guidelines, latest evidence for the airway protection equipment, the role of AED in cardiac arrest, latest advances and the evidence including ongoing updated research including return of spontaneous circulation and post resuscitation care and support including neurological and hemodynamic stability. \r\n\t \r\n\tThe content of this book will be focused on latest research in the field which will create a concise updated information for medical, nursing and paramedical personnel. Furthermore, the book will also touch upon controversial topics in resuscitation and will try to bring out latest evidence intending to solve the controversies in the field of resuscitation. This book will be an excellent extract of all available updates and ongoing research for a complete knowledge of resuscitation.
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1. Introduction
Today, a web search is clearly one of the foremost methods for finding information. The growth of the Internet and the increasing availability of online resources have made the task of searching a crucial one. However, searching the web is not always as successful as users expect it to be and Internet users have to make a great effort to formulate a search query that returns the required results. Information retrieval concentrates on developing algorithms to locate and select documents from a corpus that are relevant to a given query. The development of online information retrieval tools, such as search engines or search robots many of which utilize hyperlink analysis [1], has been greatly beneficial to Internet users [2]. In the health domain, users are now experiencing huge difficulties in finding precisely what they are looking for among the numerous documents available online, and this in spite of existing tools. In medicine and health-related information accessible on the Internet, general search engines, such as Google, or general catalogues, such as Yahoo, cannot solve this problem efficiently [3]. This is because they usually offer a selection of documents that turn out to be either too large or ill-suited to the query. Free text word-based search engines typically return innumerable completely irrelevant hits, which require much manual weeding by the user, and also miss important information resources.
In this context, several health gateways [4] have been developed to support systematic resource discovery and help users find the health information they are looking for. These information seekers may be patients but also health professionals, such as physicians searching for clinical trials. Health gateways rely on thesauri and controlled vocabularies. Some of them are evaluated in [5]. Medical thesauri are a proven key technology for effective access to health information since they provide a controlled vocabulary for indexing documents and coding electronic health records. They therefore help to overcome some of the problems of free-text search by linking and grouping terms and concepts. Nonetheless, medical vocabularies are difficult to handle by non-professionals. Problems also arise because there are practically as many different terminologies, controlled vocabularies, thesauri and classification systems as there are fields of application in health. We give in this chapter a panel of techniques that may be applied to help health information seekers. All the tests are performed on the CISMeF catalogue (Catalogue and Index of Medical Sites in French) [6] but are reproducible in other languages and other medical applications.
The remainder of the chapter is organized as follows: in section 2 we start by describing the CISMeF catalogue. The section 3 is devoted to simple search techniques such as approximate string matching and heuristics for queries composed by several words. Another method consists in meta-modeling health terminologies to improve information retrieval, the description of which is in the section 4. In the section 5 we describe the data-mining process to extract new knowledge and relations between terms to allow users to extend their searches.
2. The CISMeF catalogue
The CISMeF project was initiated in February 1995. As opposed to Yahoo, CISMeF is cataloguing the most important and quality-controlled sources of institutional health information in French. The CISMeF catalogue describes and indexes a large number of health-information resources of high quality (n=13,452 in October 2003; n=90,056 in May 2012). A resource can be a web site, web pages, documents, reports and teaching material: any support that may contain health information.
CISMeF takes into account the diversity of the end-users and allow them to find good quality resources. These resources are selected according to strict criteria by a team of librarians and are indexed according to a methodology which involves a four-fold process: resource collection, filtering, description and indexing. CISMeF is a quality-controlled gateway such as defined by Koch [4]. The following elements that characterize a typical quality-controlled health gateway are fulfilled in CISMeF: selection and collection development, collection management, intellectual creation of metadata, resource description (a metadata set), resource indexing (with controlled vocabulary system). To include only reliable resources, and to assess the quality of health information on the Internet, the main criteria (e.g. source, description, disclosure, last update) of CISMeF are from HONCode
http://www.hon.ch/
. In the following sections we describe the set of metadata elements and the reference dictionary used in the catalogue.
2.1. CISMeF metadata
The notion of metadata was around before the Internet but its importance has grown with the increasing number of electronic publications and digital libraries. The World Wide Web Consortium (W3C) have proposed that metadata should be used to describe the data contained on the web and to add semantic markup to web resources, thus describing their content and functionalities, from the vocabulary defined in terminologies and ontologies.
Metadata are data about data, and in the web context, these are data describing web resources. When properly implemented, metadata enhance information retrieval. The CISMeF uses several sets of metadata. Among them there is the Dublin Core (DC) [7] metadata set, which is a 15-element set intended to aid discovery of electronic resources. The resources indexed in CISMeF are described by eleven of the Dublin Core elements: author, date, description, format, identifier, language, editor, type of resource, rights, subject and title. DC is not a complete solution; it cannot be used to describe the quality or location of a resource. To fill these gaps, CISMeF uses its own elements to extend the DC standard. Eight elements are specific to CISMeF: institution, city, province, country, target public, access type, sponsorships, and cost. The user type is also taken into account. The CISMeF have defined two additional fields for resources intended for health professionals: indication of the evidence-based medicine, and the method used to determine it. For teaching resources, eleven elements of the IEEE 1484 LOM (Learning Object Metadata) “Educational” category are added.
2.2. CISMeF controlled vocabulary
Thesauri are a proven key technology for effective access to information as they provide a controlled vocabulary for indexing information. They therefore help to overcome some of the problems of free-text search by relating and grouping relevant terms in a specific domain. The main thesaurus used for medical information is the Medical Subject Headings (MeSH) [8] thesaurus used by the U.S. National Library of Medicine to index MEDLINE articles. The core of MeSH is a hierarchical structure that consists of sets of descriptors. At the top level we find general headings (e.g. diseases), and at deeper levels we find more specific headings (e.g. asthma). The 2012 version of the MeSH contains over 26,581 main headings (e.g. hepatitis, abdomen) and 83 subheadings (e.g. diagnosis, complications). Together with a main heading, a subheading allows to specify which particular aspect of the main heading is being addressed. For example, the pair [hepatitis/diagnosis] specifies the diagnosis aspect of hepatitis. For each main heading, MeSH defines a subset of allowable qualifiers so that only certain pairs can be used as indexing terms (e.g. aphasia/metabolism and hand/surgery are allowable, but hand/metabolism is not). The reference dictionary of CISMeF (the structure of which is detailed in Table 1) was created between 1995 and 2005 exclusively on the French version of the MeSH thesaurus maintained by the US National Library of Medicine, completed by numerous synonyms in French collected by the CISMeF team.
Several add-ons were performed around the MeSH thesaurus to index Web resources instead of scientific articles [9]: super-concepts (or Meta-terms) to optimize information retrieval and categorization, and resource types (organized hierarchically since 1997 vs. MeSH publication types’ hierarchy since 2006). Indeed, MeSH main headings and subheadings are organized hierarchically but these hierarchies do not allow a complete view concerning a specialty. The main headings and subheadings in the CISMeF controlled vocabulary are brought together under metaterms (e.g. cardiology). Metaterms (n=73) concern medical specialties and it is possible by browsing to know sets of MeSH main headings and subheadings qualifiers which are semantically related to the same specialty but dispersed in several trees. The MeSH thesaurus was originally used to index biomedical scientific articles for the MEDLINE database. In addition to the set of metaterms, the CISMeF team has modeled a hierarchy of resource types (n=127), to customize MeSH to the field of e-health resources. These resource types describe the nature of the resource (e.g. teaching material, clinical guidelines, patient forums), and are a generalization or extension of the MEDLINE publication types. Each resource in CISMeF is described with a set of MeSH main headings, subheadings and CISMeF resource types. Each main heading, [main heading/subheading] pair, and resource type is allotted a ‘minor’ or ‘major’ weight, according to the importance of the concept it refers to in the resource. Major terms are marked by a star (*).
MeSH Terms
MeSH Synonyms
CISMeF synonyms
Total
1 word
9,679
9,391
3,359
22,429
2 words
9,833
28,051
8,258
46,142
3 words
4,204
19,551
6,569
30,324
4 words and +
2,503
16,992
4,924
24,419
Table 1.
Composition of the reference dictionary based on the MeSH in French.
2.3. Searching through the catalogue
Many ways of navigation and information retrieval are possible in the catalogue [6]. The most used is the simple search (free text interface). It is based on subsumption relationships. If the query can be matched with an existing term of the terminology, thus the result is the union of the resources that are indexed by the term, and the resources that are indexed by the terms it subsumes, directly or indirectly, in all the hierarchies it belongs to. If the query cannot be matched, the search is done over the other fields of the metadata and in a worse case a full-text search is carried out. Contrary to MEDLINE, the resource types and the meta-terms were voluntary made ambiguous to maximize the recall (e.g. in the query guidelines in virology, virology will be recognized as a meta-term (instead of a term) and guidelines will be recognized as both the term and the resource type because we assume most of end users confuse content and container). In the following section we propose some simple enhancements for health information seekers\' queries matching.
3. Spell-checking queries
A simple spelling corrector, such as Google\'s "Did you mean:" or Yahoo\'s "Also try:" feature may be a valuable tool for non-professional users who may approach the medical domain in a more general way [10]. Such features can improve the performance of these tools and provide the user with the necessary help. In fact, the problem of spelling errors represents a major challenge for an information retrieval system. If the queries (composed by one or multiple words) generated by information seekers remain undetected, this can result in a lack of outcome in terms of search and retrieval. A spelling corrector may be classified in two categories. The first relies on a dictionary of well-spelled terms and selects the top candidate based on a string edit distance calculus. An approximate string matching algorithm, or a function, is required to detect errors in users\' queries. It then recommends a list of terms, from the reference dictionary, that are similar to each query word. The second category of spelling correctors uses lexical disambiguation tools in order to refine the ranking of the candidate terms that might be a correction of the misspelled query.
3.1. Related work
Several studies have been published on this subject. We cite the work of Grannis [11] which describes a method for calculating similarity in order to improve medical record linkage. This method uses different algorithms such as Jaro-Winkler, Levenshtein [12] and the longest common subsequence (LCS). In [13] the authors suggest improving the algorithm for computing Levenshtein similarity by using the frequency and length of strings. In [14] a phonetic transcription corrects users\' queries when they are misspelled but have similar pronunciation (e.g. Alzaymer vs. Alzheimer). In [15] the authors propose a simple and flexible spell-checker using efficient associative matching in a neural system and also compare their method with other commonly used spell-checkers. In fact, the problem of automatic spell checking is not new. Indeed, research in this area started in the 1960\'s [16] and many different techniques for spell-checking have been proposed since then. Some of those techniques exploit general spelling error tendencies and others exploit phonetic transcription of the misspelled term to find the correct term. The process of spell-checking can generally be divided into three steps:
error detection: the validity of a term in a language is verified and invalid terms are identified as spelling errors;
error correction: valid candidate terms from the dictionary are selected as corrections for the misspelled term;
ranking: the selected corrections are sorted in decreasing order of their likelihood of being the intended term.
Many studies have been performed to analyze the types and the tendencies of spelling errors for the English language. According to [17] spelling errors are generally divided into two types, (i) typographic errors and (ii) cognitive errors. Typographic errors occur when the correct spelling is known but the word is mistyped by mistake. These errors are mostly related to keyboard errors and therefore do not follow any linguistic criteria (58% of these errors involve adjacent keys [18] and occur because the wrong key is pressed, or two keys are pressed, or keys are pressed in the wrong order …etc.). Cognitive errors, or orthographic errors, occur when the correct spelling of a term is not known. The pronunciation of the misspelled term is similar to the pronunciation of the intended correct term. In English, the role of the sound similarity of characters is a factor that often affects error tendencies [18]. However, phonetic errors are harder to correct because they deform the word more than a single insertion, deletion or substitution. Damereau [16] indicated that 80% of all spelling errors fall into one of the following four single edit operation categories : (i) transposition of two adjacent letters (ashtma vs. asthma) (ii) insertion of one letter (asthmma vs. asthma) (iii) deletion of one letter (astma vs. asthma) and (iv) replacement of one letter by another (asthla vs. asthma). Each of these wrong operations costs 1 i.e. the distance between the misspelled and the correct word [[17].
The third step in spell-checking is the ranking of the selected corrections. Main spell-checking techniques do not provide any explicit mechanism. However, statistical techniques [19] provide ranking of the corrections based on probability scores [20] with good results [21]. HONselect [22] is a multilingual and intelligent search tool integrating heterogeneous web resources in health. In the medical domain, spell-checking is performed on the basis of a medical thesaurus by offering information seekers several medical terms, ranging from one to four differences related to the original query. Exploiting the frequency of a given term in the medical domain can also significantly improve spelling correction [23]: edit distance technique is used for correction along with term frequencies for ranking. In [24] the authors use normalization techniques, aggressive reformatting and abbreviation expansion for unrecognized words as well as spelling correction to find the closest drug names within RxNorm for drug name variants that can be found in local drug formularies. It returns only drug name suggestions. To match queries with the MeSH thesaurus, Wilbur et al. [25] proposed a technique on the noisy channel model and statistics from the PubMed logs.
3.2. Proposed method
Research has focused on several different areas, from pattern matching algorithms and dictionary searching techniques to optical character recognition of spelling corrections in different domains. However, the literature is quite sparse in the medical domain, which is a distinct problem, because of the complexity of medical vocabularies. In this section, a simple method is proposed: it combines two approximate string comparators, the well-known Levenshtein [6] edit distance and the Stoilos function similarity defined in [26] for ontologies. We apply and evaluate these two distances, alone and combined, on a set of sample queries in French submitted to the health gateway CISMeF. A set of 127,750 queries were extracted from the query log server (3 months logs). Only the most frequent queries were selected. In fact some queries are more frequent than others. For example, the query "swine flu" is more present in the query log than "chlorophyll". We eliminated the doubles (68,712 queries remained). From these 68,712 queries, we selected 25,000 queries to extract those with no answers (7,562). A set of 6,297 frequent queries was constituted from the original set of 7,562 by eliminating those that were submitted only once. In this set, the queries were composed from 1 to 4 and more words as detailed in the Table 2.
Composition
Number
1 word
1,061
2 words
1,636
3 words
1,443
4 (and more) words
2,157
Total
6,297
Table 2.
Structure of the queries (with no answer) obtained from the logs.
3.2.1. Similarity functions
Similarity functions between two text strings S1 and S2 give a similarity or dissimilarity score between S1 and S2 for approximate matching or comparison. For example, the strings "Asthma" and "Asthmatic" can be considered similar to a certain degree. Modern spell-checking tools are based on the simple Levenshtein edit distance [12] which is the most widely known. This function operates between two input strings and returns a score equivalent to the number of substitutions and deletions needed in order to transform one input string into another. It is defined as the minimum number of elementary operations that is required to pass from a string S1 to a string S2. There are three possible transactions: replacing a character with another, deleting a character and adding a character. This measure takes its values in the interval [0, ∞ [. The Normalized Levenshtein [27] (LevNorm) in the range [0,1] is obtained by dividing the distance of Levenshtein Lev(S1, S2) by the size of the longest string and it is defined by the following equation:
LevNorm(S1,S2)=Lev (S1,S2)Max(|S1|,|S2|)E1
For example, LevNorm(eutanasia, euthanasia)=0.1, as Lev(eutanasia, euthanasia)=1 (adds 1 character h); |eutanasia|=9 and |euthanasia|=10.
We complete the calculation of the Levenshtein distance by the similarity function Stoilos proposed in [26]. It has been specifically developed for strings that are labels of concepts in ontologies. It is based on the idea that the similarity between two entities is related to their commonalities as well as their differences. Thus, the similarity should be a function of both these features. It is defined by the equation (2) where Comm(S1,S2) stands for the commonality between the strings S1 and S2, Diff(S1,S2) for the difference between S1 and S2, and Winkler(S1,S2) for the improvement of the result using the method introduced by Winkler in [28]:
The function of commonality is determined by the substring function. The biggest common substring between two strings (MaxComSubString) is computed. This process is further extended by removing the common substring and by searching again for the next biggest substring until none can be identified. The function of commonality is given by the equation (3):
Comm(S1,S2)=2×∑i|MaxComSubStringi||S1|+|S2|E3
For example, for S1=Trigonocepahlie and S2=Trigonocephalie we have: |MaxComSubString1| = |Trigonocep|=10, |MaxComSubString2| =|lie|=3 and Comm(Trigonocepahlie,Trigonocephalie) = 0.866.
The difference function Diff(S1,S2) is based on the length of the unmatched strings resulting from the initial matching step. The function of difference is defined in equation (4) where p∈ [0, ∞ [,|uS1|and |uS2| represent the length of the unmatched substring from the strings S1 and S2 scaled respectively by their length :
For example for S1=Trigonocepahlie and S2=Trigonocephalie and p=0.6 we have: |uS1|= 2/15; |uS2|=2/15; Diff(S1,S2) =0.0254.
The Winkler parameter Winkler(S1,S2) is a factor that improves the results. It is defined by the equation (5) where L is the length of common prefix between the strings S1 and S2 at the start of the string up to a maximum of 4 characters and P is a constant scaling factor for how much the score is adjusted upwards for having common prefixes. The standard value for this constant in Winkler\'s work is P=0.1 :
Winkler(S1,S2)=L×P×(1−Comm(S1,S2))E5
For example, for between S1=hyperaldoterisme and S2=hyperaldosteronisme, we have |S1|=16, |S2|=19; the common substrings between S1 and S2 are hyperaldo, ter, and isme. Comm(S1,S2)=0.914; Diff(S1,S2)=0; Winkler(S1,S2)=0.034 and Sim(hyperaldoterisme,hyper aldosteronisme)=0.948.
3.2.2. Processing users\' queries
As detailed in [18], spelling errors can be classified as typographic and phonetic. Cognitive errors are caused by a writer\'s lack of knowledge and phonetic ones are due to similar pronunciation of a misspelled and corrected word. We pre-process the queries by a phonetic transcription with the algorithm described in [14]. To process multi-word queries, we used the following basic natural language processing steps and the well-known Bag-of-Words (BoW) algorithm before applying similarity functions:
Query segmentation: the query was segmented in words thanks to a list of segmentation characters and string tokenizers. This list is composed of all the non-alphanumerical characters (e.g.: * $,!§;|@).
Character normalizations: we applied two types of character normalization at this stage. MeSH terms are in the form of non-accented uppercase characters. Nevertheless, the terms used in the CISMeF terminology are in mixed-case and accented. (1) Lowercase conversion: all the uppercased characters were replaced by their lowercase version; “A” was replaced by “a”. This step was necessary because the controlled vocabulary is in lowercase. (2) Deaccenting: all accented characters (“éèêë”) were replaced by non-accented (“e”) ones. Words in the French MeSH were not accented, and words in queries were either accented or not, or wrongly accented (hèpatite” instead “hépatite”).
Stop words: we eliminated all stop words (such as the, and, when) in the query. Our stop word list was composed 1,422 elements in French (vs. 135 in PubMed).
Exact match expression: we use regular expressions to match the exact expression of each word of the query with the terminology. This step allowed us to take into account the complex terms (composed of more than one word) of the reference dictionary and also to avoid some inherent noise generated by the truncations. The query ‘accident’ is matched with the term ‘circulation\n\t\t\t\t\t\t\t\taccident’ but not with the terms ‘accidents’ and ‘chute accidentelle’. The query \'sida\' is matched with the terms \'lymphome lié sida\' and \'sida atteinte neurologique\' but not with the terms \'glucosidases\', \'agrasidae\' and \'bêta galactosidase\' which are not relevant.
Phonemisation: It converts a word into its French phonemic transcription: e.g. the query alzaymer is replaced by the reserved term alzheimer.
Bag of words: The algorithm searched the greatest set of words in the query corresponding to a reserved term. The query was segmented. The stop words were eliminated. The other words were transformed with the Phonemisation function and sorted alphabetically. The different reserved term bags were formed iteratively until there were no possible combinations. The query \'therapy of the breast cancer\' gave two reserved words: \'therapeutics\' and ‘breast cancer\' (therapy being a synonym of the reserved term therapeutics).
3.2.3. Evaluations
To evaluate our method of correcting misspellings, we used the standard measures of evaluation of information retrieval systems, by calculating precision, recall and the F-Measure. We performed a manual evaluation to determine these measures. Precision (6) measured the proportion of queries that were properly corrected among those corrected.
The F-Measure combined the precision and recall by the following equation (8) :
F−Measure=2×Precision×Recall(Precision+Recall)E8
We also calculated confidence intervals at =5% to avoid evaluating the whole set of queries, but some sets that are manually manageable. For a proportion x and a set of size nx the confidence interval is:
CIx=[x−1.96×x×(1−x)nx;x+1.96×x×(1−x)nx]E9
3.2.4. Results
The Levenshtein and Stoilos functions require a choice of thresholds to obtain a manageable number of correction suggestions for the user. We tested, in a previous work, different thresholds [29] for the normalized Levenshtein distance, the similarity function of Stoilos and for the combination of both on a set of 163 queries. The best results were obtained with Levenshtein>0.2 and Stoilos>0.7. To determine the impact of the size of the query we measured the number of suggestions of corrected queries (on the set of 6,297 frequent queries) in the Table 3. For a user, the maximum number of manageable suggestions for one query was 6.
Nb characters
Nb suggestions by query
1 word query
Min = 3; Avg = 10.49 ; Max = 25
Avg = 0.39 ; Max = 5
2 words query
Min = 5; Avg = 18.36; Max = 41
Avg = 0.22 ; Max = 6
3 words query
Min = 10; Avg = 24.39; Max = 54
Avg = 0.13; Max = 1
4 words and +query
Min = 11; Avg = 37.30; Max = 113
Avg = 0.06; Max = 1
Table 3.
Number of suggestions according to the size of the queries.
Manual evaluations were performed on sets of ~1/3 of each type of queries. Evaluations of the quality of queries suggestions (Precision, Recall and F-Measure) were performed manually on several sets, according to the size of the query, but also according to the following methods : Bag-of-Words, Levenshtein distance alongside the Stoilos similarity function, but also the Bag-of-Words processed before and after the combination of the Levenshtein distance along with the Stoilos similarity function. Levenshtein and Stoilos remained constant at <0.2 and >0.7 respectively. The resulting curves are in Figures 1, 2 and 3. By combining the Bag-of-Words algorithm along with the Levenshtein distance and the similarity function of Stoilos, a total of 1,418 (22.52 %) queries matched medical terms or combinations of medical terms. The remaining queries with no suggestions (when terms and also the possible combination of terms) not belong to the dictionary. For 1-word queries, it remained 711 (67%), for 2-words queries it remained 1197 queries (73.16%); for 3-words queries it remained 1126 (78.08%) and for 4 words queries it remained 1,846 queries (85.58%). For example, the query "nutrithérapie" (nutritherapy) contains no error but cannot be matched with any medical term in the reference dictionary. Evaluations shown that best results were obtained by performing the Bag-of-Words algorithm before the combination of Levenshtein alongside Stoilos.
Figure 1.
Precision curves according to the size of the query.
Figure 2.
Recall curves according to the size of the query.
The different experiments we performed show that with 38% recall and 42% precision, Phonemisation cannot correct all errors : it can only be applied when the query and entry term of the vocabulary have similar pronunciation. However, when there is reversal of characters in the query, it is an error of another type: the sound is not the same and similarity distances such as Levenshtein and Stoilos can be exploited here. Similarly, when using certain characters instead of others ("ammidale" instead of "amygdale"), string similarity functions are not efficient. The best results (F-measure 64.18%) are obtained with multi-word queries by performing the Bag-of-Words algorithm first and then the spelling-correction based on similarity measures. Due to the relatively small number of correction suggestions (min 1 and max 6), which are manually manageable by a health information seeker, we have chosen to return an alphabetically sorted list rather than ranking them.
Figure 3.
F-Measure curves according to the size of the query.
3.3. Simple heuristics
The complex terms matching is more requiring than simple terms matching. The CISMeF team editorial policy concerning the queries\' rewriting consists in maximizing as much as possible the Doc\'CISMeF recall. This approach is mainly due to the size of the CISMeF\'s corpus (n=90,056 vs. several million in the MEDLINE database). When all the terms of the query couldn\'t be recognized as reserved terms or couldn\'t be corrected by our spell-checker, we have implemented 5 main heuristics:
The reserved terms: The process consists in recognizing the user query expression. If it matches a reserved term of the terminology, the process stops, and the answer of the query is the union of the resources that are indexed by the term, and the resources that are indexed by the terms it subsumes, directly or indirectly, in all the hierarchies it belongs to. If it doesn\'t match a reserved term, the query is segmented into seek if it contains one or more reserved terms. The query \'enfant asthme\' is replaced by the Boolean query (enfant.mr AND asthme.mr), where enfant and asthme are reserved terms (mr). The reserved terms are matched thanks to the bag of words algorithm independently of the words query order.
The documents\' title: The search is performed over the other fields of the metadata. The title of the documents is considered in priority. The stop words are eliminated and the search is realized over the union of the words of the query with a truncation (*) at the right in the field title (ti), as the following: word1*.ti AND word2*.ti for a 2-words query.
Mixing the reserved terms and the titles: The system seeks if some words are reserved terms or not. A new Boolean query is generated with the fields reserved term (mr), if the word is a reserved term, and title (ti) if not. The query \'allergie infantile\' is replaced by the Boolean query (allergie.mr AND infantile.ti).
Mixing the reserved terms, all fields and adjacency in the titles : The search is processed over all the fields (tc) of the documents\' metadata for the words that couldn\'t be recognized as reserved terms UNION the initial query processed over all the fields with adjacency (at) at n words with n=5*(nb words of the query-1). The query \'les problems respiratoires des enfants\' is replaced by the Boolean query [(enfant.mr AND problemes.tc AND respiratoires.tc ) OR (problemes respiratoires enfant.at)]. In this query, the word enfant is recognized as a reserved term because it has the same sonority as the reserved term enfants. The words problèmes and respiratoires are searched over all the fields and the initial query problèmes respiratoires enfants is searched over all the fields with adjacency of 10 which means that these 3 words shouldn\'t be distant at more than 10 words.
Mixing the reserved terms, all fields and adjacency in the plain texts : A plain text search over the documents with adjacency (ap) of n words with n=10*(nb words of the query-1) is realized. The query \'bronchite asthmatiforme\' is replaced by the Boolean query (bronchite asthmatiforme.ap) where the words bronchite and asthmatiforme shouldn\'t be distant at more than 10 words in the plain texts of the documents.
An intuitive scale of interpretation (from Step 1 to Step 5) is available to inform the users about their queries operations and rewritings. By using these simple heuristics, 65% of the queries returned documents (27% by the step 1; 7% by the step 2; 4% by the step 3; 10% by the step 4 and 17% by the step 5).
We describe in the next section how to maximize information retrieval by meta-modeling. The relevance on using multiple medical terminologies to improve information retrieval versus only the MeSH thesaurus is also evaluated.
4. Meta-modeling
To maximize information retrieval through the catalogue, one another enhancement is to gather all the MeSH terms that are related to a given specialty, since they can be dispersed among the 16 MeSH branches. On the other hand, the use of multiple terminologies is recommended [29] to increase the number of the lexical and graphical forms of a biomedical term recognized by a search engine. Since 2007, the CISMeF resources are indexed using the vocabulary of 23 other terminologies and classifications, most of them being bilingual (English and French). To supply health information seekers with the terminologies available in French, these terminologies are accessible through the Health Multiple Terminologies and Ontologies Portal (HeTOP) [31].
4.1. MeSH meta-terms for information retrieval
The MeSH thesaurus is partitioned at its upper level into 16 branches (e.g. Anatomy, Diseases). The core of MeSH thesaurus is a hierarchical structure that consists of sets of descriptors. However, these hierarchies do not allow a complete view concerning a specialty. The main headings and subheadings in the CISMeF controlled vocabulary are gathered under meta-terms (e.g. cardiology) (Figure 4). Meta-terms (n=73) concern medical specialties and it is possible by browsing to know sets of MeSH main headings and subheadings which are semantically related to the same specialty but dispersed in several trees. Meta-terms have been created to optimize information retrieval in CISMeF and to overcome the relatively restrictive nature of MeSH headings. For example a search on “guidelines” or “virology”, where cardiology and virology are descriptors, yield few answers. Introducing cardiology and virology as meta-terms is an efficient strategy to obtain more results because instead of exploding one single MeSH tree, the use of meta-terms results in an automatic expansion of the queries by exploding other related MeSH trees besides the current tree, using the well-known automatic query expansion process. In other words, a query using a meta-term corresponds to the union of all the queries for all the terms semantically linked to it. A comparison of the results of MeSH term-based queries and SC-based queries showed an increased recall with no decrease in precision [33].
4.2. Multiple-terminologies meta-terms
The use of multiple terminologies is recommended [29] to increase the number of the lexical and graphical forms of a biomedical term recognized by a search engine. For this reason, CISMeF evolved recently from a single terminology approach using the MeSH main headings and subheadings to a multiple terminologies paradigm using, in addition to the MeSH thesaurus, vocabularies and classifications that deal with various aspects of health. Among them, the Systematized NOmenclature of MEDicine (SNOMED 3.5), the French CCAM for procedures [34], Orphanet for rare diseases
www.orpha.net
and some classifications from the World Health Organization : the 10th revision of the International Classification of Diseases
http://www.who.int/classifications/icd/en/
(ICD10), Anatomical Therapeutic Chemical (ATC) Classification for drugs, ICF for handicap, ICPS for patient safety, MedDRA
http://www.meddramsso.com
for adverse effects. These terminologies were fully integrated into the CISMeF back-office. They can be used for indexing resources (allowing a more precise indexing) and thus for querying the catalogue. However, the addition of multiple terminologies to CISMeF did not induce modifications in the tasks performed for using, maintaining and updating the catalogue. The richest source of biomedical terminologies, thesauri, classifications is constituted by the Unified Medical Language System (UMLS) Metathesaurus initiated in by the U.S. NLM with the purpose to integrate information from a variety of sources. Nonetheless, the Metathesaurus does not allow interoperability between terminologies since it integrates the various terminologies as they stand without making any connection between the terms in the terminologies other than by linking equivalent terms to a single identifier in the Metathesaurus. The approach in CISMeF has the advantage of combining respect for the original structure of each of the terminologies with a re-grouping of the meta-data inherent in each terminology.
New terminologies have been linked to meta-terms manually by experts in CISMeF: one physician for ICD10, which is partitioned into 22 chapters, and the CCAM; one pharmacist-librarian for ATC, and one medical resident for the terms of the Foundational Model of Anatomy. For instance, the meta-term "cardiology" was initially linked to MeSH main headings such as "cardiology", "stents", and their descendants. With the integration of new terminologies, additional links completed the definition of the meta-term “cardiology”: links to "cardiovascular system", "Antithrombotic agents" and others from ATC, links to "Cardio-myopathy", "Heart" and their descendants from ICD10 and so on.
4.2.1. Test queries
Our aim is to compare the precision and recall of multiple terminologies meta-terms (mt-mt) to MeSH meta-terms (M-mt) in CISMeF. Since mt-mt are based on M-mt plus semantic links to some terms in other terminologies, the query results for M-mt are all included in the query results for mt-mt, which became the gold standard for recall. We have then to evaluate the precision of the query retrieving resources indexed by a term linked to M-mt (MeSH meta-term query), on the one hand, and by a term linked to mt-mt and not to M-mt ( query) on the other hand. For this purpose, we build Boolean queries using the meta-terms themselves. For example, for the "surgery" meta-term, the MeSH meta-term (M-mt) query is "surgery[M-mt]". The query is: "surgery[mt-mt] NOT surgery[M-mt]". Retrieved resources returned were assessed for relevance. We detail in the next section the criteria we have used for evaluation.
4.2.2. Evaluations
The resources returned by the CISMeF\'s search tool using automatic query expansion were assessed for relevance according to a three modality scale used in other standard Information Retrieval test sets: irrelevant (0), partly relevant (1) or fully relevant (2). A physician manually assigned relevance scores (0;1;2) to the top 20 resources returned for each meta-term query. The results of the evaluation are given in the Table 4. We chose to assign relevance scores to the top twenty resources returned because 95% of the end-users do not go beyond this limit when using a general search engine [35]. For the purpose of assessing meta-terms for Information Retrieval, we have developed a test collection comprising relevance judgments for the top 20 resources returned for a selection of 20 eta-terms queries. Table 4 shows that the queries yielded 118,772 resources, of which 708 were assessed for relevance (0.6%). Weighted precisions for MeSH meta-terms queries and for queries were computed given the level of relevance considered and compared using χ² test. Indexing methods and meta-terms were compared too. Relative recall for MeSH meta-terms queries were computed given the level of relevance considered.
Figure 4.
Gathering MeSH main headings and subheadings under meta-terms. Resource types are modelled to describe the nature of a resource because of the heterogeneity of resources.
The mean weighted precision of queries was 0.33 and 0.76 for, respectively, full and partial relevance. The mean precision of MeSH meta-terms queries was 0.66 and 0.80 for, respectively, full and partial relevance. The difference between MeSH meta-terms and multiple terminologies meta-terms was significant for full relevance (0.66 vs 0.61; p<10-4, χ²) but not for partial relevance (both 0.80; p=0.3, χ²). The mean recall of MeSH meta-terms queries was 0.92 and 0.86 for, respectively, full and partial relevance. Table 5 shows that, whatever the relevance considered was, results varied significantly according to the indexing method: manual (precision of 0.50 and 0.81 for, respectively, full and partial relevance) perform better than automatic (precision of 0.38 and 0.48 for, respectively, full and partial relevance), and to the studied meta-term.
Figure 5.
Relevance of resources retrieved by 18 meta-terms queries on top 20 documents.
Figure 6.
Determinants of relevance; χ² test.
To complete the information retrieval process and to allow interactive query expansion with the health information seeker, we propose in the next section to use "new" knowledge represented as association rules extracted by data-mining process.
5. Knowledge extraction
The knowledge-approach is based upon a data-mining process, called association rules, which can infer "new" relations between medical concepts. A data-mining system may generate several thousands and even several millions frequent association rules, and only some of these will be interesting. In this section we will show how only the most relevant association rules are mined using Formal Concept Analysis and Galois closure. We consider a relevant association rule as being non-redundant with a minimal antecedent and a maximal consequent, which is particularly useful for query expansion.
5.1. Association rules
The discovery of association rules is a widely used technique in data-mining. The general problem was described in [36], in which relations were discovered among pieces of data (called items). An association rule is interesting if it is easily understood by the users, valid for new data, useful, or confirms a hypothesis. The task of association rule mining can be applied to various types of data: any data set containing multiple items.
5.1.1. Definitions
Let I be a set of items, called itemset, and D a database of transactions where each transaction T (T\n\t\t\t\t\t\tD) is an itemset. An association rule is an implication rule expressed in the form of: I1→I2 where I1 and I2 are two itemsets I1, I2\n\t\t\t\t\t\tI so that I1 ∩ I2 =. The rule expresses that whenever a transaction T contains I1 then T probably also contains I2. In other words, the implication rule means that the apparition of the itemset I1 in a transaction T, implies the apparition of the itemset I2 in the same transaction. However, the reciprocal implication does not have to happen necessarily. I1 is called antecedent and I2 is called consequent.
5.1.2. Support
The support of an association rule represents its utility. This measure corresponds to the proportion of objects which contains at the same time the rule antecedent and consequent. It is possible to calculate the support of an association rule from the support of an itemset. Supp(Ik) the support of the itemset Ik is defined as the probability of finding Ik in a transaction of T:
Supp(Ik)=|{t∈T/Ik⊆t}||T|E10
The support of the rule I1→I2 written as Supp(I1→I2) is calculated as follows:
Supp(I2→I1)=Supp(I1∪I2)E11
5.1.3. Confidence
The confidence of an association rule represents its precision. This measure corresponds to the proportion of objects that contains the consequent rule among those containing the antecedent. The confidence of the rule I1→I2, written as Conf(I1→I2) is calculated as follows:
Conf(I1→I2)=Supp(I1∪I2)Supp(I1)E12
Two types of rules are distinguished: exact association rules that have a confidence equal to 100%, i.e. verified in all the objects of the database and approximate association rules that confidence<100%.
5.2. Data-mining algorithms
Several methods are used to extract all of the association rules from a database. The simplest method consists of enumerating all the itemsets from which all the possible association rules could be generated. The total number of itemsets for a database that contains n Boolean attributes is 2n. This naïve method is inapplicable to real-life databases. A more efficient method involves computing itemsets that have a support higher than a given threshold. They are called frequent itemsets. The association rules extraction time depends on the frequent itemsets extraction time. Several accesses to the database are necessary to compute the number of database objects in which each frequent itemset candidate is contained. The association rules algorithms by level consider in each iteration a set of itemsets of a particular size, i.e. a set of itemsets in a level of the itemsets lattice. The following properties are used by these algorithms to limit the number of the itemsets candidates: all of the super-sets of an infrequent itemset are infrequent, and all the subsets of a frequent itemset are frequents [37]. This method is founded on the two-stepped model that finds all of the rules that satisfy user-specified minimum support and confidence: (i) Generate all large itemsets that satisfy minimum support and (ii) From large itemests generate all association rules that satisfy minimum confidence. Apriori algorithm [37] realizes a number of database accesses equal to the size of the larger frequent itemsets. Many researchers have tried to improve various aspects of Apriori, such as the number of passes and accesses to the data-bases or the time efficiency of those passes. We have chosen to adapt the A-Close algorithm [38] in which new bases for association rules are deduced from the closed frequent itemsets and their generators. These bases consist of non-redundant association rules of minimal antecedents and maximal consequents, i.e. the most relevant association rules and are defined by using the closure operator of the Galois connection of a finite binary relation. All frequent itemsets and their support, and therefore all association rules, are deduced efficiently from the frequent closed itemsets without accessing the database.
5.3. Extracting knowledge from e-Health documents
Our experiments are carried out on the CISMeF database. An extraction context is a triplet C= (O, I, R) where O is the set of objects, I is the set of all the items and R is a binary relation between O and I. Applying this model to our database, the objects are the indexed e-health documents. Each document has a unique identifier and a set of associated descriptors. These descriptors may be MeSH main headings and associations between MeSH main headings and MeSH subheadings. The relation R represents the indexing relation between an object and an item, i.e. a descriptor that belongs to I. We studied different extraction contexts by applying and adapting the A-Close algorithm such as the context of categorized documents, according to the user type and to meta-terms. There is an average of 6.5 descriptors by document in CISMeF with a minimum of 1 and a maximum of 300. This constraint on the number of descriptors i.e. the size of the set of items has been considered in the implementation phase of the A-Close algorithm. Indeed, A-Close works on databases with a maximum of 12 items. We have added another requirement to the implementation to avoid long time generation: maximal size of the closed itemsets is fixed to 300 items as it corresponds to the maximum number of descriptors for the documents. As an output, the association rules may be visualized in a file or automatically added to the database to be used in the information retrieval process, mainly by interactive query expansion.
5.3.1. Extracting knowledge from all the database
Case 1: In the first case, let I be the set of main headings (MH), which, via R, are used to index a subset O of 11,373 documents. The 11,373 documents were selected at random. We have fixed the support threshold as minsup=20 and the confidence threshold as minconf=70%. A total of 11,819 rules were mined (2,438 exact with confidence=100%; 9,381 approximate with confidence≥70%). The number of rules is too high to be manually analyzed by our experts (physicians or medical librarians).
Case 2: In the second case, let I be the set of main headings (MH) and subheadings (SH) associated with the set of documents O. I={MH}{SH}. We obtained 16,976 rules (5,241 exact; 11,738 approximate). The same conclusions are drowned from the case 1 : too numerous rules to be evaluated manually.
Case 3: In the third case, I is the set of the associations of main headings and subheadings (MH/SH) related to the documents. I={[MH/SH]}. Association rules between couples of (MH/SH) are more precise than association rules between main headings, and between main headings and subheadings since a subheading specifies a particular aspect of a main heading. With the same thresholds as in cases 1 and 2, the number of rules is 2,565 (648 exact rules; 1,917 approximate rules).
The extracted association rules in the precedent cases are related to the medical domain. To obtain more precise rules we performed experiments on categorized documents according to groups of users: students in medicine, health professionals, and general public to evaluate the influence of categorization on the generation of association rules.
5.4. Categorizing documents according to health information seekers
In CISMeF, mainly three types of health information seekers are categorized: professionals, students in medicine, patients and lay people. We consider three major resource types: guidelines*, education* and patients*. We also consider two kinds of itemsets: the set of major main headings I={MH*} and the set of major (main heading/subheading) pairs I={[MH/SH]*)}. The collection is detailed in Table 6.
Resource type
Documents
Items
Min
Max
Mean
Guidelines*
2,727
MH*
1
64
5.21
MH/SH*
1
70
6.12
Patients*
3,272
MH*
0
25
1.63
MH/SH*
0
30
1.82
Education*
3,610
MH*
0
25
2.22
MH/SH*
0
34
2.73
Table 4.
Description of the collections of documents.
For all contexts, the minimum support threshold was fixed to minsup=20 and the minimum confidence threshold was fixed to minconf=70% (Table 7). We obtained association rules between major main headings MH* in the first context where I={MH*} and between [MH/SH]* pairs for I={[MH/SH]*}. For the major resource types patients* and education* all association rules (100%) are between two MHs* and between [MH/SH]* i.e. one descriptor in the antecedent and one descriptor in the consequent. For the major resource type guidelines*, 24% of the rules are between more than two descriptors. The characteristics of documents may explain these results: average descriptors were from 1.63 to 2.22 for patients* and education* whereas they were from 5.21 to 6.12 for guidelines*.
Resource types
Item=MH*
Item=[MH/SH]*
Nb rules
ER
AR
Nb pairs
Nb rules
ER
AR
Nb pairs
Guidelines*
50
12
38
38
39
8
31
35
24%
76%
76%
20.51%
79.49%
76%
Patients*
20
9
11
20
19
8
11
19
45%
55%
100%
42.1%
57.9%
100%
Education*
23
6
17
23
25
13
12
25
26.09%
73.91%
100%
52%
48%
100%
Table 5.
Number of rules, exact rules (ER), approximate rules (AR), and number of pairs.
5.4.1. Evaluation of the extracted knowledge
Not all of the association rules extracted were evaluated: according to the context extraction and the itemset I there are more or less association rules. The more the collection is specialized, and the itemset size is reduced, the less we have association rules to evaluate. As defined, an interesting association rule confirms or states a new hypothesis [38].
Here, we proposed to combine background domain knowledge with simple statistical measures used traditionally in association rules mining for evaluation. We considered several cases of interesting association rules according to relations between MeSH headings. As these relations are defined between two main headings and between two subheadings, we considered only the association rules between two elements. Hence, an interesting existing association rule could associate: a (in)direct son and its father (relation FS); two descriptors that belong to the same hierarchy (same (in)direct father) (relation BR); two descriptors with See Also relation (relation SA). These rules are automatically classified thanks to the MeSH structure. The other rules that satisfy the minsup and minconf are then considered as «new» interesting association rules.
Exact association rules, except for collection patients*, are mostly new interesting rules: from 62.5% to 87.4%. Therefore, existing rules are mainly from the patients* collection: 77.8% for MH* and 75% for MH/SH*. However, approximate rules, are mostly existing rules (Table 8). Subjective interest measures are based on expert knowledge about the data, i.e. that of physicians and medical librarians in this context. New interesting rules for the contexts MH* and [MH/SH]* pairs are evaluated manually. 93.8% (resp. 84.8%) of the interesting new rules with conf=1 (resp. conf≥0.7) between major descriptors are validated.
Resource types
Items
Exact rules
Approximate rules
Existing knowledge
New
Existing knowledge
New
FS
BR
SA
FS
BR
SA
Guidelines*
MH*
-
-
4 33.3%
8 66.7%
2 5.3%
7 18.4%
10 26.3%
12 31.6%
MH/SH*
1 12.5%
1 12.5%
1 12.5%
5 62.5%
3 9.7%
3 9.7%
9 29%
13 42%
Patients*
MH*
-
5 55.6%
2 22.2%
2 22.2%
2 18.2%
2 18.2%
4 36.3%
3 27.3%
MH/SH*
-
5 62.5%
1 12.5%
2 25%
2 18.2%
2 18.2%
3 27.3%
7 36.3%
Education*
MH*
1 16.7%
1 16.7%
-
4 66.6%
2 11.8%
6 35.3%
3 17.6%
6 35.3%
MH/SH*
1 7.7%
-
1 7.7%
11 87.4%
2 16.8%
3 25%
2 16.8%
5 41.4%
Table 6.
Association rules evaluation according to the MeSH structure
5.5. Knowledge-based query expansion
Our objective is to re-use the numerous association rules that we extracted from the CISMeF database into the information-retrieval process by query expansion. We use Interactive Query Expansion. For example, the association rule breast cancer → mammography is extracted from the corpus because the keywords breast cancer and mammography are frequently used together to index the documents. This association rule is as a “new” one because it doesn’t exist in the domain knowledge which is, in our case, the MeSH thesaurus. When applying the association rule breast cancer → mammography on a query containing the term breast cancer, an interactive query expansion proposes to the user e-health documents related to mammography to complete the search. In medicine and health-related information, [40] have already investigated an efficient algorithm for association rule mining using the MeSH thesaurus. They adopted a MeSH-indexed representation of MEDLINE records, but the evaluation of the interest of the mined associations with respect to the task of PubMed retrieval improvement was not considered by the authors. In [41] many other works on information retrieval and query expansion in the biomedical domain are also presented. Methods to perform query expansion with promising results involve mining user logs [41] and constructing user profiles. And another study on logs in PubMed for searching biomedical and life-science literature online has been performed by [43].
In the literature, a number of methods for performing query expansion have been developed. The solutions given are based mainly on two approaches. The first is the augmentation of query terms to improve the retrieval process without user intervention. The second is the suggestion of new terms to the user which can to be added to the original query to guide the search towards a more specific document space. The first case is called automatic query expansion whereas the second case is called semi-automatic query-expansion. In [44], the authors tried to evaluate and compare the efficiency of the two methods. Despite the fact that their experiments were based on simulations and not on real human users in most of the cases, the results of the experiments showed that the interactive query expansion method gave more control to the searcher who knows her utility better than any automated system. Researchers also turned to methods such as lexical co-occurrence [45]. Lexical co-occurrence is the process of developing relationships between words based upon their co-occurrence in documents. The similarity of the method we have proposed here with lexical co-occurrence is that the source, which provides the candidate terms for expansion, is the set of the retrieved documents as opposed to some knowledge structure as in thesaurus-based approaches. As a consequence, if the user chooses terms that do not yield results from the expected domain, the terms suggested by the query-expansion algorithm are unlikely to be helpful to the user. A solution may be a simple spell-checker.
5.6. Evaluating query expansion based on association rules
Many ways of navigation and information retrieval are possible in the catalogue. The most used is the simple search (free text interface). As stated in the section 2, it is based on the subsumption relationships. A query (a word or an expression) can be matched with an existing concept. In this case, the result of the query is the union of the resources that are indexed by the concept, and the resources that are indexed by the concepts it subsumes, directly or indirectly, in all of the hierarchies it belongs to. The co-occurrence tools developed for information retrieval bring the terms which frequently appear in the same documents closer together. These terms thus have a semantic proximity. This technique was used very early to allow query expansion. By analogy, association rules may be exploited in a search engine by carrying out an interactive query expansion. This helps the user to formulate his query by using the result of a query to reformulate, filter and re-orientate the query by exploiting the terms related to his query terms. In fact, the user can select suggested terms sets to add them to his initial query. It is useful in the case of non-precise information needs. IQE requires user implication. We developed a web-based evaluation tool of the IQE used by a set of 500 users which are subscribers of the weekly letter “What’s new” of CISMeF. 20 queries, and for each one a set of medical terms derived from the extracted association rules were proposed. The evaluation was performed thanks to a Likert scale. The results (76% of the users were satisfied by the propositions) demonstrate the usefulness of this approach. An expanded query by association rules contains more related terms. By using the vectorial model, for example, more documents will be located and this treatment increases recall. In addition, association rules are indication on the possible definition of a term or its context.
6. Conclusions
We have presented in this chapter useful methods to help health information seekers to find resources on the Internet which is the most popular way used nowadays. The experiences were carried out on the CISMeF catalogue in French, but are reproducible for other e-health applications in other languages. These methods include simple ones such as heuristics and spell-checking, and more sophisticated ones such as knowledge extraction from e-health documents.
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Darmoni",authors:[{id:"143224",title:"Dr.",name:"Lina",middleName:"F",surname:"Soualmia",fullName:"Lina Soualmia",slug:"lina-soualmia",email:"lina.soualmia@gmail.com",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/143224/images/3336_n.jpg",institution:null},{id:"162665",title:"MSc.",name:"Badisse",middleName:null,surname:"Dahamna",fullName:"Badisse Dahamna",slug:"badisse-dahamna",email:"badisse@chu-rouen.fr",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"162666",title:"Prof.",name:"Stéfan J",middleName:null,surname:"Darmoni",fullName:"Stéfan J Darmoni",slug:"stefan-j-darmoni",email:"stefan.darmoni@chu-rouen.fr",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. The CISMeF catalogue",level:"1"},{id:"sec_2_2",title:"2.1. CISMeF metadata",level:"2"},{id:"sec_3_2",title:"2.2. CISMeF controlled vocabulary",level:"2"},{id:"sec_4_2",title:"2.3. Searching through the catalogue",level:"2"},{id:"sec_6",title:"3. Spell-checking queries",level:"1"},{id:"sec_6_2",title:"3.1. Related work",level:"2"},{id:"sec_7_2",title:"3.2. Proposed method",level:"2"},{id:"sec_7_3",title:"3.2.1. Similarity functions",level:"3"},{id:"sec_8_3",title:"3.2.2. Processing users' queries",level:"3"},{id:"sec_9_3",title:"3.2.3. Evaluations",level:"3"},{id:"sec_10_3",title:"Table 3.",level:"3"},{id:"sec_12_2",title:"3.3. Simple heuristics",level:"2"},{id:"sec_14",title:"4. Meta-modeling",level:"1"},{id:"sec_14_2",title:"4.1. MeSH meta-terms for information retrieval",level:"2"},{id:"sec_15_2",title:"4.2. Multiple-terminologies meta-terms",level:"2"},{id:"sec_15_3",title:"4.2.1. Test queries",level:"3"},{id:"sec_16_3",title:"4.2.2. Evaluations",level:"3"},{id:"sec_19",title:"5. Knowledge extraction",level:"1"},{id:"sec_19_2",title:"5.1. Association rules",level:"2"},{id:"sec_19_3",title:"5.1.1. Definitions",level:"3"},{id:"sec_20_3",title:"5.1.2. Support",level:"3"},{id:"sec_21_3",title:"5.1.3. Confidence",level:"3"},{id:"sec_23_2",title:"5.2. Data-mining algorithms",level:"2"},{id:"sec_24_2",title:"5.3. Extracting knowledge from e-Health documents",level:"2"},{id:"sec_24_3",title:"5.3.1. Extracting knowledge from all the database",level:"3"},{id:"sec_26_2",title:"5.4. Categorizing documents according to health information seekers",level:"2"},{id:"sec_26_3",title:"Table 6.",level:"3"},{id:"sec_28_2",title:"5.5. Knowledge-based query expansion",level:"2"},{id:"sec_29_2",title:"5.6. Evaluating query expansion based on association rules",level:"2"},{id:"sec_31",title:"6. Conclusions",level:"1"}],chapterReferences:[{id:"B1",body:'HouJ.ZhangY.Effectively finding relevant web pages from linkage information. 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1. Introduction
There are numerous theories with regards to the aetiology of acute appendicitis. These theories include genetic factors, environmental influences, luminal obstruction and infections. However, of all these theories, the debate between luminal obstruction with possible secondary infective process and primary infective causes has been the fiercest. With the latter raising more questions than answers.
Even though many infectious agents have been linked with acute appendicitis, quite a number of them are still unknown and this makes the understanding of the pathophysiology even more difficult [1, 2, 3]. In addition to the aforementioned, most organisms isolated from patients are typically normal colonic flora and that is in sharp contrast to the original postulation of the temporal and geographic distribution of organisms.
Luminal obstruction of the appendix results from a variety of causes and is associated with increased pressure within the lumen. Causes of appendiceal luminal obstruction include lymphoid hyperplasia due to inflammatory bowel disease or infections (commonly viruses), parasites, foreign bodies, neoplasms and faecoliths. The increased pressure results from continuous secretion and stagnation of fluids and mucus from the mucosal epithelial cells. This serves to provide a conducive milieu for intestinal flora to multiply and flourish. This multiplication leads to local increase in bacteria load, with its accompanying translocation and the subsequent inflammatory process which ensues, resulting in the formation of pus and a further increase in intraluminal pressure.
Appendiceal venous outflow obstruction occurs as the intraluminal pressure rises above the appendiceal venous pressure. A further increase in luminal pressure also impairs arterial blood flow to the appendix. The above-mentioned vascular compromise gives rise to a loss of epithelial integrity and wall ischaemia, which in addition to the luminal bacteria overgrowth, and rapid bacteria translocation are often complicated by peritonitis, perforation, gangrene of the appendix and/or peri-appendicular abscess with or without peritonitis.
2. Faecoliths as a causal agent of acute appendicitis
Faecolith, also known as appendicolith, appendiceal calculi/enterolith or corpolith, is a combination of firm, dense stool and mineral or calcified deposits which usually has a laminar structure [4]. Although the formation of a faecolith is not clearly understood, there have been previous instances where foreign bodies and gallstones have been implicated [5, 6]. As a matter of fact, for a long time, there was a myth which seemed to have suggested that accidental swallowing of seeds could cause acute appendicitis.
Early on, faecoliths were noted to be one of the most common causes of acute appendicitis resulting from luminal obstruction. In the early 19th century Volz observed faecoliths to be a “pathognomonic agent” for typhlitis [7]. Later that century, Fitz revealed that in patients who presented with perforated appendicitis, 47% of them had hardened stools in the lumen of the appendix [8]. These findings raised enough suspicions which linked faecoliths to acute appendicitis and possibly its complicated forms. As a result, many other observations were published [9, 10, 11]. Most of these studies, however, remained experimental until Bowers conclusively showed in the late 1930s that obstruction by a faecolith was a major cause of acute appendicitis [12].
The other issue with respect to faecoliths in acute appendicitis has to do with its consistency. This has led to the suggestion that faecoliths should be classified based on consistency and calcium content due to their correlation with perforation. On the contrary, other authors have also suggested that even the softer form presents more commonly with appendicitis than the harder ones [13, 14].
In fact, the prevalence of faecoliths in the vermiform appendix has been recently reported to be 3% in a population study by Jones et al. [15]. In this study, the investigators observed an increased incidence in populations with increased intake of low-fibre diets. Other studies have shown higher prevalence in paediatric and young adult population, with increased male preponderance [16]. There are also reports of increased incidence of faecoliths among patients with a retrocaecal appendix, but these are yet to be substantiated.
From the discussions so far, it can therefore be concluded that the presence of faecoliths does not confirm a diagnosis of acute appendicitis without the presence of appendiceal wall inflammation involving the muscularis propria on histological assessment or peri-caecal inflammatory changes/appendiceal wall enhancement clinically. On this matter, there have been numerous conflicting reports on the relationship between the presence of faecoliths and appendicitis especially in different age groups [17, 18, 19]. There are reports by some authors that up to 49% appendices with luminal obstruction were normal on histological assessment. The same study also found that 49% of appendices with luminal obstruction had microscopic evidence of acute inflammation even though they looked normal macroscopically. Some of these studies initially led to the performance of an appendicectomy in asymptomatic patients with a faecolith by some surgeons. This practice, however, is currently controversial. At the moment, the widely accepted evidence is what Butler et al. [20] reported. They found faecoliths in 10% of patients, with 90% of them subsequently going on to develop appendicitis. The purpose of this chapter is however to look at the effect of faecoliths on the disease process of acute appendicitis.
The discussion on the role of faecoliths in appendicitis, in general, could be as old as the disease process itself and as result many theories have been postulated in times past. This chapter will be broken down into subheadings on important aspects of the role of faecoliths in acute appendicitis.
3. Incidence and diagnosis
The incidence of faecoliths in population and patient studies have been generally discussed in previous paragraphs of this chapter. With the introduction of modern abdominal imaging modalities from plain abdominal radiography, ultrasound examination, computed tomography (CT) scan to magnetic resonance imaging, the association of faecoliths as an important cause of luminal obstruction in acute appendicitis have become very clear and recent data reports prevalence of about 20% in pathological specimens either with or without the presence of acute appendicitis.
Faecoliths are usually one the main causes of non-specific intermittent abdominal pain. In some cases, it even mimics genitourinary conditions such as urolithiasis. They are usually less than a centimeter in diameter and those that are more than two-centimeters are classified as giant faecoliths. Even though those greater than two-centimeters are considered uncommon, the largest ever recorded is 3.5 cm [21, 22].
A study by Ishiyama et al. [23] to investigate the significance of appendicoliths as an exacerbating factor of acute appendicitis using multivariate analysis resulted in very interesting findings. First of all, they were able to show that the presence of a faecolith is usually associated with more severe disease. In addition, the study identified a significant relationship between severe disease and size, and location of the faecolith. The larger the size and/or the more proximal the location in the vermiform appendix, the more likelihood of severe disease. The radiological characteristics of faecoliths associated with acute appendicitis were recently described by Khan [24]. He and his colleagues concluded that, in addition to a faecolith of 5 millimetres or more, multiple faecoliths were also identified to be an independent factor associated with acute appendicitis.
The diagnosis of acute appendicitis in a patient who presents with abdominal pain has markedly improved with the advent of numerous imaging modalities. In the presence of a faecolith, an abdominal plain radiography study alone can be considered as adequate when there is associated abdominal pain, with a specificity of 100% [25]. The use of CT scans in the assessment of patients suspected to have appendicitis has shown that the incidence of faecoliths is higher in the general population than previously reported. Two studies by Balthazar et al. and Rao et al. reports of incidence between 43 and 50% in predominantly adult patients diagnosed with acute appendicitis [26, 27]. In the paediatric population, Lowe and her friends showed that the incidence of faecoliths in patients with confirmed acute appendicitis was 65% [28]. This detection rate could be diminished by the administration of oral contrast. CT scans have been extensively used in the diagnosis of acute appendicitis.
At the time of writing this chapter, there was no study or literature dedicated to the diagnostic capabilities of ultrasound (US) scan in faecolith-related acute appendicitis. However, in general, the accuracy of US scan in the diagnosis of acute appendicitis is between 71–95% with sensitivity and specificity of 94.7% and 88.9% respectively when graded compression ultrasonography is done [29, 30]. Magnetic Resonance Imaging (MRI) has the advantage of no ionizing radiation exposure and the absence of nephrotoxic contrast agents. Availability and cost are among the main reasons why it is underutilised, although it has a sensitivity and specificity of 96.8% and 97.4% respectively. At the moment, there is very little data on its role and position in the workup of appendicitis, except in very special circumstances [31].
4. Role of faecoliths in disease presentation and failure of conservative treatment
Literature on what role and effect faecoliths have on clinical scoring systems in acute appendicitis was very scanty to come by and therefore this chapter cannot provide a comment on that currently. Nonetheless, some studies, like that of Ishiyama and colleagues as mentioned in the previous paragraph have observed severe disease presentations in patient with faecoliths compared to those without.
In addition, faecoliths have been known to be more frequently associated with perforations and abscess formation [32]. Flum et al. found that the presence of faecoliths was identified to be a significant contributor of post treatment complications and adverse effects in patients who received antibiotics alone compared with those who had surgery. They also realised that though the perforation rate was high in patients initially treated with antibiotics, this high rate was attributable to patients with a faecolith. They reported about a 3-fold rise in perforations among the faecolith group. This, however, did not lead to a higher rate of extensive resections in the antibiotic group. Looking at the group that had appendicectomy done as initial treatment, there was not much difference in the perforation rate between patients with faecoliths and those without.
As a result, the finding of an appendicolith may be sufficient evidence to perform an appendectomy in patients earmarked for conservative management, given the higher rate of perforation at the time of failure of antibiotic treatment. This position is so explicitly stated in the recommendations made in the Jerusalem guidelines of 2020 and seems to be consistent with what Von and his friends found. It is however the author’s strong believe that every patient’s situation should be uniquely assessed, and a tailored treatment advocated with the patient’s express consent of course.
5. Effect on treatment and complications
In the management of acute uncomplicated appendicitis using laparoscopy, Finnerty et al. [33] showed that age, presence of diabetes, raised BMI, presence of imaging confirmed complicated appendicitis, male gender and ethnicity were independent predictor of failure in laparoscopic management of acute uncomplicated appendicitis. At the moment, there is no evidence to support which method of treatment is best in the presence of faecolith in acute uncomplicated appendicitis, even though current evidence favours laparoscopy in the management of uncomplicated acute appendicitis generally. The presence of faecolith has been shown to have significant effect on therapeutic interventions and therefore the treating surgeon must be informed about the presence of faecolith for certain considerations to be taken into account. For instance, there have been several studies and case reports to show that dropped faecolith is a major contributor of post interventional morbidity with increased incidence of pelvic abscesses especially after laparoscopic appendicectomy.
The results from the CODA trial showed a noninferiority in managing patient with acute appendicitis conservatively with antibiotics in terms of 30-day post treatment health status, which was the primary outcome of the study. At 90-day post treatment, 29% of patients in the antibiotic arm had undergone appendicectomy. When a subgroup analysis was done, the number of patients with faecolith who required appendicectomy in the antibiotic group was almost twice patients without faecolith in the same subgroup. Even though all these are evolving areas of controversy, the surgeon’s awareness of the presence of faecolith is key to enable adequate decision making and planning for possible retrieval of faecolith if so needed [32, 34, 35].
6. Faecolith as a predictor for extensive resection
The Gridiron incision, also known as McBurney’s incision, is the most commonly used open method in the management of acute uncomplicated appendicitis. In addition to this type of incision offering a minimally invasive and direct access to the diseased appendix, it provide good cosmesis and in lean (healthy BMI) patients, it is usually comparable to laparoscopic technique in terms of access, time of surgery, hospital stay and cosmetic advantage. In situations of delayed presentation or complications, McBurney’s technique becomes extremely challenging and, in such situations, larger laparotomy incisions are made with accompanied extensive bowel resection in some cases. The most common extensive bowel resection in acute appendicitis is ileocaecectomy with or without primary anastomosis of bowel. Recent evidence suggests that appendiceal mass, non-visualization of appendix, delayed admission, and CRP are strong predictors of extensive resection in acute appendicitis [36]. Additionally, faecolith was also identified as a preoperative predictor of extensive resection for acute appendicitis. Other preoperative predictors of extensive resection found in these studies included age, ascites, and extraluminal air. The role of faecolith in predicting the possibility of extensive resection obviously require further robust research but should not be underestimated.
7. Role of routine interval appendectomy in the presence of faecoliths
Consensus on routine interval appendicectomy after conservative management of acute appendicitis is another highly debated subtopic in acute appendicitis. As a principle, surgeons are more inclined to do routine interval appendicectomy especially in patients in their mid-forties and above as there is an increased risk of malignancy in this groups. However, one can question the essence of this practice especially when there are very accurate diagnostic imaging modalities available to assist with confirming the presence of a tumour. While some have argued for routine interval appendicectomy when a faecolith is involved because of its possible association with increase recurrence rate, others have suggested otherwise as there have not been adequate evidence to support this idea especially when patients remained asymptomatic [37, 38].
To conclude, the role of faecoliths in causing acute appendicitis, and not just the disease but the worse form of it cannot be underestimated. Its ability to accelerate complications in the disease process and in addition cause significant headaches for surgeons and patients cannot be in dispute. The several contrasting opinions with regards to what to do with it confirms how complicated the situation is. It is the author’s firm opinion that more focused research should be done on this subject. Also, a lot of commendations should go to the designers and authors of the CODA trial who have thrown more light on this subgroup of patients.
\n',keywords:"Faecolith, Appendicitis",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/76153.pdf",chapterXML:"https://mts.intechopen.com/source/xml/76153.xml",downloadPdfUrl:"/chapter/pdf-download/76153",previewPdfUrl:"/chapter/pdf-preview/76153",totalDownloads:108,totalViews:0,totalCrossrefCites:0,dateSubmitted:"February 13th 2021",dateReviewed:"March 19th 2021",datePrePublished:"October 2nd 2021",datePublished:"January 12th 2022",dateFinished:"April 8th 2021",readingETA:"0",abstract:"Luminal obstruction has been widely considered as one of the major causes of appendicitis. Faecolith, in this case called appendicolith, is a hardened lump of faeces in varying sizes, have over the years been closely associated with appendicitis as a potential cause of luminal obstruction. There are varying opinions with regards to role of appendicolith in both uncomplicated and complicated acute appendicitis. While some authors have reported that the presence of appendicolith is a predictive factor for high failure rates, others are of the opinion that appendicolith does not necessarily predict non-operative treatment failure, and even if so, not as an independent factor. Opinions also seem to be divided on the correlation between complicated appendicitis and the presence of appendicolith. This chapter seeks to discuss the evidence available and attempt to clarify the controversies surrounding the role of appendicolith in acute appendicitis using current evidence available.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/76153",risUrl:"/chapter/ris/76153",signatures:"Rossi Adu-Gyamfi",book:{id:"10316",type:"book",title:"Doubts, Problems and Certainties about Acute Appendicitis",subtitle:null,fullTitle:"Doubts, Problems and Certainties about Acute Appendicitis",slug:"doubts-problems-and-certainties-about-acute-appendicitis",publishedDate:"January 12th 2022",bookSignature:"Angelo Guttadauro",coverURL:"https://cdn.intechopen.com/books/images_new/10316.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",isbn:"978-1-83968-856-0",printIsbn:"978-1-83968-855-3",pdfIsbn:"978-1-83968-857-7",isAvailableForWebshopOrdering:!0,editors:[{id:"239365",title:"M.D.",name:"Angelo",middleName:null,surname:"Guttadauro",slug:"angelo-guttadauro",fullName:"Angelo Guttadauro"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"333676",title:"Dr.",name:"Rossi",middleName:null,surname:"Adu-Gyamfi",fullName:"Rossi Adu-Gyamfi",slug:"rossi-adu-gyamfi",email:"drpaoloross@gmail.com",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/333676/images/14654_n.jpg",institution:{name:"Stellenbosch University",institutionURL:null,country:{name:"South Africa"}}}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Faecoliths as a causal agent of acute appendicitis",level:"1"},{id:"sec_3",title:"3. Incidence and diagnosis",level:"1"},{id:"sec_4",title:"4. Role of faecoliths in disease presentation and failure of conservative treatment",level:"1"},{id:"sec_5",title:"5. Effect on treatment and complications",level:"1"},{id:"sec_6",title:"6. Faecolith as a predictor for extensive resection",level:"1"},{id:"sec_7",title:"7. Role of routine interval appendectomy in the presence of faecoliths",level:"1"}],chapterReferences:[{id:"B1",body:'Lamps LW. Infectious causes of appendicitis. Infect Dis Clin North Am 2010; 24: 995-1018'},{id:"B2",body:'Dzabic M, Bostrom L, Rahbar A. High prevalence of an active cytomegalovirus infection in the appendix of immunocompetent patients with acute appendicitis. Inflamm Bowel Dis 2008; 14: 236-41'},{id:"B3",body:'Carr NJ. The pathology of acute appendicitis. Ann Diagn Pathol 2000; 4: 46-58'},{id:"B4",body:'Felson B, Bernhard CM. Roentgenologic diagnosis of appendiceal calculi. Radiology 1947; 49:178-91'},{id:"B5",body:'Mehrotra PK, Ramachandran CS, Gupta L. Laparoscopic management of gallstone presenting as obstructive gangrenous appendicitis. J Laparoendosc Adv Surg Tech A 2005; 15:627-9'},{id:"B6",body:'Moorjani V, Wong C, Lam A. Ingested foreign body mimicking an appendicolith in a child. Br J Radiol 2006; 79:173-4'},{id:"B7",body:'Volz A. Die durch Kothsteine bedingte Durchbohrung des Wurmfortsatzes, die häufig verkannte Ursache einer gefährlichen Peritonitis, und deren Behandlung mit Opium. Carlsruhe, Germany: CF Müller; 1846'},{id:"B8",body:'Fitz RH. Perforating inflammation of the vermiform appendix. Am J Med Sci 1886; 92: 321-346'},{id:"B9",body:'Van Zwalenburg C. The relation of mechanical distention to the etiology of appendicitis. Ann Surg 1905; 41: 437-450'},{id:"B10",body:'Van Zwalenburg C. Appendicitis: some points in its diagnosis and treatment from the view-point that its cause is a strangulation produced by distension behind a ball-valve. Cal State J Med 1905; 3: 14-16'},{id:"B11",body:'Wangensteen OH, Dennis C. Experimental proof of the obstructive origin of appendicitis in man. Ann Surg 1939; 110: 629-647'},{id:"B12",body:'Forbes GB, Lloyd-Davies RW. Calculous disease of the vermiform appendix. Gut. 1966; 7: 583-592'},{id:"B13",body:'Sgourakis G, Sotiropoulos GC, Molmenti EP et al. Are acute exacerbations of chronic inflammatory appendicitis triggered by coprostasis and/or coproliths? World J Gastroenterol 2008; 14: 3,179-3,182'},{id:"B14",body:'Bowers WF. Appendicitis with especial reference to pathogenesis, bacteriology and healing. Arch Surg 1939; 39: 362-422'},{id:"B15",body:'Jones BA, Demetriades D, Segal I, Burkitt DP. The prevalence of appendiceal fecaliths in patients with and without appendicitis. A comparative study from Canada and South Africa. Ann Surg. 1985; 202:80-2'},{id:"B16",body:'Nitecki S, Karmeli R, Sarr MG. Appendiceal calculi and fecaliths as indications for appendectomy. Surg Gynecol Obstet. 1990; 171:185-8'},{id:"B17",body:'Huwart L, El Khoury M, Lesavre A, Phan C, Rangheard AS, Bessoud B et al. Is appendicolith a reliable sign for acute appendicitis at MDCT? J Radiol 2006; 87:383-7'},{id:"B18",body:'Jabra AA, Shalaby-Rana EI, Fishman EK. CT of appendicitis in children. J Comput Assist Tomogr 1997; 21:661-6'},{id:"B19",body:'Aljefri A, Al-Nakshabandi N. The stranded stone: Relationship between acute appendicitis and appendicolith. Saudi J Gastroenterol 2009;15:258-60'},{id:"B20",body:'Butler P, Mitchell A, Healy JC. Applied Radiological Anatomy. Cambridge University Press. (2012) ISBN:0521766664'},{id:"B21",body:'Keating JP, Memon S. Giant appendicolith. Gastrointest Endosc 2005; 61:292-3'},{id:"B22",body:'Felson B, Bernhard CM. Roentgenologic diagnosis of appendiceal calculi. Radiology 1947; 49:178-91'},{id:"B23",body:'Ishiyama M, Yanase F, Taketa T, Makidono A, Suzuki K, Omata F, et al. Significance of size and location of appendicoliths as exacerbating factor of acute appendicitis. Emerg Radiol 2013; 20:125-30'},{id:"B24",body:'Khan M, Chaudhry M, Shahzad N, et al. (August 05, 2019) The Characteristics of Appendicoliths Associated with Acute Appendicitis. Cureus 11(8): e5322. DOI 10.7759/cureus.5322'},{id:"B25",body:'Kirks DR. The gastrointestinal tract. In: Practical pediatric imaging: diagnostic radiology of infants and children. Philadelphia: Lippincott- Raven, 1995:945-952'},{id:"B26",body:'Balthazar EJ, Birnbaum BA, Yee J, Megibow AJ, Roshkow J, Gray C. Acute appendicitis: CT and US correlation in 100 patients. Radiology 1994; 190:31-35'},{id:"B27",body:'Rao PM, Rhea JT, Novelline RA. Sensitivity and specificity of the individual CT signs of appendicitis: experience with 200 helical appendiceal CT examinations. J Comput Assist Tomogr 1997;21: 686-692'},{id:"B28",body:'Lowe LH, Penney MW, Scheker LE, Perez Jr. R, Stein SM, Heller RM, Shyr Y, Hermanz-Schulman M. Appendicolith Revealed on CT in Children with Suspected Appendicitis: How Specific Is It in the Diagnosis of Appendicitis? AJR 2000; 175:981-984'},{id:"B29",body:'Rao PM, Boland GWL. Imaging of acute right lower abdominal quadrant pain. Clin Radiol 1998; 53:639ˇ49'},{id:"B30",body:'Douglas CD, Macpherson NE, Davidson PM, Gani JS. Randomised controlled trial of ultrasonography in diagnosis of acute appendicitis, incorporating the Alvarado score. BMJ 2000; 321:1-7'},{id:"B31",body:'Kulaylat AN, Moore MM, Engbrecht BW, et al. An implemented MRI program to eliminate radiation from the evaluation of pediatric appendicitis. J Pediatr Surg 2015;50(8):1359-63'},{id:"B32",body:'Flum DR, Davidson GH, Monsell SE, et al. A Randomized Trial Comparing Antibiotics with Appendectomy for Appendicitis: The CODA Collaborative. NEJM 2020; 383(20): 1907-1919'},{id:"B33",body:'Finnerty BM, Wu X, Giambrone GP, Gaber-Baylis LK, Zabih R, et al. Conversion-to-open in laparoscopic appendectomy: A cohort analysis of risk factors and outcomes. International Journal of Surgery. 2017;40: 169-175'},{id:"B34",body:'Itah R, Skornick Y, Greenberg R. Extraluminal appendicolith: An indication for interval appendectomy with intraoperative localization and removal of that potential cause of intra-abdominal abscess. J Laparoendosc Adv Surg Tech A 2008; 18:606-8'},{id:"B35",body:'Singh AK, Hahn PF, Gervais D, Vijayraghavan G, Mueller PR. Dropped appendicolith: CT findings and implications for management. AJR Am J Roentgenol 2008; 190:707-11'},{id:"B36",body:'Saida F, Matsumoto S, Kitano M. Preoperative predictor of extensive resection for acute appendicitis. The American Journal of Surgery. 2018;215: 599-602'},{id:"B37",body:'Rushing A, Bugaev N, Jones C, MD, Como JJ, Fox N, et al. Management of acute appendicitis in adults: A practice management guideline from the Eastern Association for the Surgery of Trauma. J Trauma Acute Care Surg. 2019;87: 214-224'},{id:"B38",body:'Vons C, Barry C, Maitre S, Pautrat K, Leconte M, Costaglioli B, Karoui M, Alves A, Dousset B, Valleur P, et al. Amoxicillin plus clavulanic acid versus appendectomy for treatment of acute uncomplicated appendicitis: an openlabel, noninferiority, randomized controlled trial. Lancet. 2011;377: 1573-1579'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Rossi Adu-Gyamfi",address:"drpaoloross@gmail.com",affiliation:'
Division of Surgery, Stellenbosch University/Tygerberg Academic Hospital, South Africa
Division of Surgery, 37 Military Hospital, Ghana
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He achieved his education in the fields of laser physics, optics, infrared technology, and light modulation and detection. He earned his MSc degree for research on laser-plasma source for lithography and micro- and nano-structures production with the lobster-eye optics assembly. He continued his education at Czech Technical University in Prague. He earned his PhD for construction, examination and applications of high-order harmonics source using titanium-sapphire femtosecond laser system and noble gases. Amongst others he expanded his professional skills to such areas like vacuum technology, spectroscopy, plasma physics, ultrafast laser systems, and optics. He started his professional career as R&D Engineer with the Academy of Sciences of the Czech Republic. Then he got involved in HiLASE Project, as Deputy Project Manager, and led the R&D team Research Program Leader working on development of thin-disk lasers. Finally, he decided to pursue an industrial career in medical devices (intraocular lenses). He worked as Head of Engineering Department with Croma Polska Ltd (now Valeant Pharmaceuticals), Warsaw, Poland. Currently he is an advisor to investors and Polish State on commercialization of innovations in life sciences. He also runs his own optoelectronics company, Perspectiva Solutions. 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In that a vaccine is a pharmaceutical product, vaccine development and production are costly and it takes years for this to be accomplished. Several approaches have been applied to reduce the times and costs of vaccine development, mainly focusing on the selection of appropriate antigens or antigenic structures, carriers, and adjuvants. One of these approaches is the incorporation of bioinformatics methods and analyses into vaccine development. This chapter provides an overview of the application of bioinformatics strategies in vaccine design and development, supplying some successful examples of vaccines in which bioinformatics has furnished a cutting edge in their development. Reverse vaccinology, immunoinformatics, and structural vaccinology are described and addressed in the design and development of specific vaccines against infectious diseases caused by bacteria, viruses, and parasites. These include some emerging or re‐emerging infectious diseases, as well as therapeutic vaccines to fight cancer, allergies, and substance abuse, which have been facilitated and improved by using bioinformatics tools or which are under development based on bioinformatics strategies.",book:{id:"5892",slug:"vaccines",title:"Vaccines",fullTitle:"Vaccines"},signatures:"Ribas‐Aparicio Rosa María, Castelán‐Vega Juan Arturo, Jiménez‐\nAlberto Alicia, Monterrubio‐López Gloria Paulina and Aparicio‐\nOzores Gerardo",authors:[{id:"193147",title:"Dr.",name:"Rosa María",middleName:null,surname:"Ribas-Aparicio",slug:"rosa-maria-ribas-aparicio",fullName:"Rosa María Ribas-Aparicio"},{id:"201116",title:"Dr.",name:"Juan Arturo",middleName:null,surname:"Castelán-Vega",slug:"juan-arturo-castelan-vega",fullName:"Juan Arturo Castelán-Vega"},{id:"201117",title:"Dr.",name:"Alicia",middleName:null,surname:"Jiménez-Alberto",slug:"alicia-jimenez-alberto",fullName:"Alicia Jiménez-Alberto"},{id:"201118",title:"Dr.",name:"Gloria Paulina",middleName:null,surname:"Monterrubio-López",slug:"gloria-paulina-monterrubio-lopez",fullName:"Gloria Paulina Monterrubio-López"},{id:"201119",title:"Dr.",name:"Gerardo",middleName:null,surname:"Aparicio-Ozores",slug:"gerardo-aparicio-ozores",fullName:"Gerardo Aparicio-Ozores"}]},{id:"65813",doi:"10.5772/intechopen.84626",title:"Vaccine Types",slug:"vaccine-types",totalDownloads:1580,totalCrossrefCites:4,totalDimensionsCites:10,abstract:"There are several different types of vaccines. Each type is designed to teach your immune system how to fight off certain kinds of germs and the serious diseases they cause. There are four main types of vaccines: live attenuated vaccines; inactivated vaccines; subunit, recombinant, polysaccharide, and conjugate vaccines; and toxoid vaccines.",book:{id:"8079",slug:"vaccines-the-history-and-future",title:"Vaccines",fullTitle:"Vaccines - the History and Future"},signatures:"Xiaoxia Dai, Yongmin Xiong, Na Li and Can Jian",authors:[{id:"276337",title:"Dr.",name:"Xiaoxia",middleName:null,surname:"Dai",slug:"xiaoxia-dai",fullName:"Xiaoxia Dai"},{id:"290421",title:"Dr.",name:"Yongmin",middleName:null,surname:"Xiong",slug:"yongmin-xiong",fullName:"Yongmin Xiong"},{id:"290422",title:"Dr.",name:"Na",middleName:null,surname:"Li",slug:"na-li",fullName:"Na Li"},{id:"290424",title:"Dr.",name:"Can",middleName:null,surname:"Jian",slug:"can-jian",fullName:"Can Jian"}]},{id:"55860",doi:"10.5772/intechopen.69547",title:"Biotechnologies Applied in Biomedical Vaccines",slug:"biotechnologies-applied-in-biomedical-vaccines",totalDownloads:3110,totalCrossrefCites:5,totalDimensionsCites:7,abstract:"Vaccination, the administration of an antigenic material (vaccine), is considered to be the most effective method for disease prevention and control. A vaccine usually contains an agent that resembles a diseases‐causing pathogen and is often made from inactivated microbes, live attenuated microbes, its toxins, or part of surface antigens (subunit). However, the modern biotechnological tools and genomics have opened a new era to develop novel vaccines and many products are successfully marketing around the world. It is important to formulate and deliver these vaccines appropriately to maximize the potential advances in prevention, therapy, and vaccinology. New vaccines employing biotechnological innovations are helping us to change the way for illness prevention. The clinical application of vaccines will be diversified along with the development of biotechnologies. In modern society, the outbreak of many infectious diseases has decreased through vaccination, but the burden of noninfectious diseases is growing. The new biotechnologies may result in not only the appreciation of vaccines which are critical in inducing protection against an infectious disease but also the production of therapeutic vaccines which are effective for alldiseases including infectious and noninfectious diseases.",book:{id:"5892",slug:"vaccines",title:"Vaccines",fullTitle:"Vaccines"},signatures:"Yuan‐Chuan Chen, Hwei‐Fang Cheng, Yi‐Chen Yang and Ming‐\nKung Yeh",authors:[{id:"180299",title:"Dr.",name:"Ming-Kung",middleName:null,surname:"Yeh",slug:"ming-kung-yeh",fullName:"Ming-Kung Yeh"},{id:"185559",title:"Dr.",name:"Yuan-Chuan",middleName:null,surname:"Chen",slug:"yuan-chuan-chen",fullName:"Yuan-Chuan Chen"},{id:"185560",title:"Dr.",name:"Hwei-Fang",middleName:null,surname:"Cheng",slug:"hwei-fang-cheng",fullName:"Hwei-Fang Cheng"},{id:"185561",title:"Dr.",name:"Yi-Chen",middleName:null,surname:"Yang",slug:"yi-chen-yang",fullName:"Yi-Chen Yang"}]},{id:"55384",doi:"10.5772/intechopen.68890",title:"Cocoon Strategy of Vaccinations: Benefits and Limitations",slug:"cocoon-strategy-of-vaccinations-benefits-and-limitations",totalDownloads:1619,totalCrossrefCites:5,totalDimensionsCites:5,abstract:"A cocoon vaccination strategy refers to vaccinations in persons from the immediate environment of those patients who might develop an illness (they are susceptible to illnesses) but cannot be vaccinated due to permanent or temporary medical contraindications to a vaccination (e.g. immunosuppressed patients) or are too young to have a vaccination. Most frequently, a cocoon vaccination strategy is associated with vaccinations in adults aimed at preventing the spread of an illness in children (e.g. pertussis vaccination or influenza vaccination), but it is worth considering whether this strategy should not be understood also as vaccinations in children with the view of protecting adults and the elderly against illnesses (e.g. influenza or pneumococcal diseases). The aim of the cocoon strategy is to minimize the risk of the transmission of pathogens in the environment of a patient who is susceptible to an infection. A vaccinated patient is not a source of infection any more for a non-vaccinated patient. The chapter presents a history, current implementation of the strategy in different countries, its benefits and limitations.",book:{id:"5892",slug:"vaccines",title:"Vaccines",fullTitle:"Vaccines"},signatures:"Aneta Nitsch-Osuch",authors:[{id:"199131",title:"Associate Prof.",name:"Aneta",middleName:null,surname:"Nitsch-Osuch",slug:"aneta-nitsch-osuch",fullName:"Aneta Nitsch-Osuch"}]},{id:"77035",doi:"10.5772/intechopen.98378",title:"Introduction on Monoclonal Antibodies",slug:"introduction-on-monoclonal-antibodies",totalDownloads:714,totalCrossrefCites:0,totalDimensionsCites:3,abstract:"Monoclonal antibodies (mAbs) are a group of antibodies produced by identical clones of B lymphocytes against a particular antigen. mAbs are identical in several properties such as protein sequence, antigen-binding site region, binding affinity for their targets, and identical downstream functional effects. These characteristics of mAbs highlight their differences with the polyclonal antibodies which have heterogenous activities and recognize different epitopes on an antigen. Murine mAbs was the first generation of mAbs developed by hybridoma technology however, because of their murine origin, they can trigger the anti-mouse antibody response in the host which could accelerate mAb clearance and undesirable allergic reactions upon repeated administration. This issue was resolved by developing engineering methods toward producing less immunologic chimeric or humanized antibodies. mAbs applications have become a novel way of targeting antigens in a wide variety of diseases such as autoimmunity, malignancies, and asthma. In addition, high specificity and high affinity binding properties of mAbs make them effective biological reagents in immunodiagnostic assays. They can be used in diagnosis of infectious diseases and detection of certain antigens or in serological assessments for detection of antibodies against a certain antigen. This chapter summarizes the general properties of mAbs, their production processes, and their important diagnostic and therapeutic applications.",book:{id:"8043",slug:"monoclonal-antibodies",title:"Monoclonal Antibodies",fullTitle:"Monoclonal Antibodies"},signatures:"Mona Sadeghalvad and Nima Rezaei",authors:[{id:"116250",title:"Dr.",name:"Nima",middleName:null,surname:"Rezaei",slug:"nima-rezaei",fullName:"Nima Rezaei"},{id:"353771",title:null,name:"Mona",middleName:null,surname:"Sadeghalvad",slug:"mona-sadeghalvad",fullName:"Mona Sadeghalvad"}]}],mostDownloadedChaptersLast30Days:[{id:"66363",title:"GMO Regulatory Aspects of Novel Investigational Vaccine Candidates",slug:"gmo-regulatory-aspects-of-novel-investigational-vaccine-candidates",totalDownloads:1834,totalCrossrefCites:1,totalDimensionsCites:1,abstract:"Recent scientific and technical developments create novel opportunities for vaccine development. Regulatory compliance has to be ensured from preclinical research to market authorization, whereby different legal frameworks that go beyond quality, efficacy or patient safety aspects need to be taken into account. As academia and start-ups are often focused on gathering scientific evidence, the regulatory maze is often regarded by applicants as challenging in the overall pathway to clinical translation. This is particularly true for applications concerning vaccine candidates containing or consisting of genetically modified organisms (GMOs). Active communication between applicants and competent authorities or advisory bodies early in the development stages facilitates a correct implementation of the regulatory frameworks and is of utmost importance to identify challenges or hurdles in order to avoid unnecessary delay in scientific review. Based on the state-of-play in Belgium, this chapter discusses examples of regulatory journeys of applications with genetically modified viral vectors and novel vaccine candidates that have been reviewed by GMO national competent authorities in Belgium and in Europe. They highlight the need of having a comprehensive view of global perspectives early in the development to facilitate the translation of research to clinical development or even market authorization.",book:{id:"8079",slug:"vaccines-the-history-and-future",title:"Vaccines",fullTitle:"Vaccines - the History and Future"},signatures:"Amaya Leunda and Katia Pauwels",authors:[{id:"281429",title:"Ph.D.",name:"Amaya",middleName:null,surname:"Leunda",slug:"amaya-leunda",fullName:"Amaya Leunda"},{id:"281703",title:"Dr.",name:"Katia",middleName:null,surname:"Pauwels",slug:"katia-pauwels",fullName:"Katia Pauwels"}]},{id:"55860",title:"Biotechnologies Applied in Biomedical Vaccines",slug:"biotechnologies-applied-in-biomedical-vaccines",totalDownloads:3110,totalCrossrefCites:5,totalDimensionsCites:7,abstract:"Vaccination, the administration of an antigenic material (vaccine), is considered to be the most effective method for disease prevention and control. A vaccine usually contains an agent that resembles a diseases‐causing pathogen and is often made from inactivated microbes, live attenuated microbes, its toxins, or part of surface antigens (subunit). However, the modern biotechnological tools and genomics have opened a new era to develop novel vaccines and many products are successfully marketing around the world. It is important to formulate and deliver these vaccines appropriately to maximize the potential advances in prevention, therapy, and vaccinology. New vaccines employing biotechnological innovations are helping us to change the way for illness prevention. The clinical application of vaccines will be diversified along with the development of biotechnologies. In modern society, the outbreak of many infectious diseases has decreased through vaccination, but the burden of noninfectious diseases is growing. The new biotechnologies may result in not only the appreciation of vaccines which are critical in inducing protection against an infectious disease but also the production of therapeutic vaccines which are effective for alldiseases including infectious and noninfectious diseases.",book:{id:"5892",slug:"vaccines",title:"Vaccines",fullTitle:"Vaccines"},signatures:"Yuan‐Chuan Chen, Hwei‐Fang Cheng, Yi‐Chen Yang and Ming‐\nKung Yeh",authors:[{id:"180299",title:"Dr.",name:"Ming-Kung",middleName:null,surname:"Yeh",slug:"ming-kung-yeh",fullName:"Ming-Kung Yeh"},{id:"185559",title:"Dr.",name:"Yuan-Chuan",middleName:null,surname:"Chen",slug:"yuan-chuan-chen",fullName:"Yuan-Chuan Chen"},{id:"185560",title:"Dr.",name:"Hwei-Fang",middleName:null,surname:"Cheng",slug:"hwei-fang-cheng",fullName:"Hwei-Fang Cheng"},{id:"185561",title:"Dr.",name:"Yi-Chen",middleName:null,surname:"Yang",slug:"yi-chen-yang",fullName:"Yi-Chen Yang"}]},{id:"77035",title:"Introduction on Monoclonal Antibodies",slug:"introduction-on-monoclonal-antibodies",totalDownloads:714,totalCrossrefCites:0,totalDimensionsCites:3,abstract:"Monoclonal antibodies (mAbs) are a group of antibodies produced by identical clones of B lymphocytes against a particular antigen. mAbs are identical in several properties such as protein sequence, antigen-binding site region, binding affinity for their targets, and identical downstream functional effects. These characteristics of mAbs highlight their differences with the polyclonal antibodies which have heterogenous activities and recognize different epitopes on an antigen. Murine mAbs was the first generation of mAbs developed by hybridoma technology however, because of their murine origin, they can trigger the anti-mouse antibody response in the host which could accelerate mAb clearance and undesirable allergic reactions upon repeated administration. This issue was resolved by developing engineering methods toward producing less immunologic chimeric or humanized antibodies. mAbs applications have become a novel way of targeting antigens in a wide variety of diseases such as autoimmunity, malignancies, and asthma. In addition, high specificity and high affinity binding properties of mAbs make them effective biological reagents in immunodiagnostic assays. They can be used in diagnosis of infectious diseases and detection of certain antigens or in serological assessments for detection of antibodies against a certain antigen. This chapter summarizes the general properties of mAbs, their production processes, and their important diagnostic and therapeutic applications.",book:{id:"8043",slug:"monoclonal-antibodies",title:"Monoclonal Antibodies",fullTitle:"Monoclonal Antibodies"},signatures:"Mona Sadeghalvad and Nima Rezaei",authors:[{id:"116250",title:"Dr.",name:"Nima",middleName:null,surname:"Rezaei",slug:"nima-rezaei",fullName:"Nima Rezaei"},{id:"353771",title:null,name:"Mona",middleName:null,surname:"Sadeghalvad",slug:"mona-sadeghalvad",fullName:"Mona Sadeghalvad"}]},{id:"65813",title:"Vaccine Types",slug:"vaccine-types",totalDownloads:1580,totalCrossrefCites:4,totalDimensionsCites:10,abstract:"There are several different types of vaccines. 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He owns the patent for herbal preparation and producing, and for the supercritical fluid-treated needle. Dr. Hu has published three books, 12 book chapters, and more than 30 papers in reputed journals, besides serving as an editorial board member of repute.",institutionString:"Kaohsiung Chang Gung Memorial Hospital",institution:{name:"Kaohsiung Chang Gung Memorial Hospital",country:{name:"Taiwan"}}},{id:"298472",title:"Prof.",name:"Andrey V.",middleName:null,surname:"Grechko",slug:"andrey-v.-grechko",fullName:"Andrey V. Grechko",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/298472/images/system/298472.png",biography:"Andrey Vyacheslavovich Grechko, Ph.D., Professor, is a Corresponding Member of the Russian Academy of Sciences. He graduated from the Semashko Moscow Medical Institute (Semashko National Research Institute of Public Health) with a degree in Medicine (1998), the Clinical Department of Dermatovenerology (2000), and received a second higher education in Psychology (2009). Professor A.V. Grechko held the position of Сhief Physician of the Central Clinical Hospital in Moscow. He worked as a professor at the faculty and was engaged in scientific research at the Medical University. Starting in 2013, he has been the initiator of the creation of the Federal Scientific and Clinical Center for Intensive Care and Rehabilitology, Moscow, Russian Federation, where he also serves as Director since 2015. He has many years of experience in research and teaching in various fields of medicine, is an author/co-author of more than 200 scientific publications, 13 patents, 15 medical books/chapters, including Chapter in Book «Metabolomics», IntechOpen, 2020 «Metabolomic Discovery of Microbiota Dysfunction as the Cause of Pathology».",institutionString:"Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology",institution:null},{id:"199461",title:"Prof.",name:"Natalia V.",middleName:null,surname:"Beloborodova",slug:"natalia-v.-beloborodova",fullName:"Natalia V. Beloborodova",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/199461/images/system/199461.jpg",biography:'Natalia Vladimirovna Beloborodova was educated at the Pirogov Russian National Research Medical University, with a degree in pediatrics in 1980, a Ph.D. in 1987, and a specialization in Clinical Microbiology from First Moscow State Medical University in 2004. She has been a Professor since 1996. Currently, she is the Head of the Laboratory of Metabolism, a division of the Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology, Moscow, Russian Federation. N.V. Beloborodova has many years of clinical experience in the field of intensive care and surgery. She studies infectious complications and sepsis. She initiated a series of interdisciplinary clinical and experimental studies based on the concept of integrating human metabolism and its microbiota. Her scientific achievements are widely known: she is the recipient of the Marie E. Coates Award \\"Best lecturer-scientist\\" Gustafsson Fund, Karolinska Institutes, Stockholm, Sweden, and the International Sepsis Forum Award, Pasteur Institute, Paris, France (2014), etc. Professor N.V. Beloborodova wrote 210 papers, five books, 10 chapters and has edited four books.',institutionString:"Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology",institution:null},{id:"354260",title:"Ph.D.",name:"Tércio Elyan",middleName:"Azevedo",surname:"Azevedo Martins",slug:"tercio-elyan-azevedo-martins",fullName:"Tércio Elyan Azevedo Martins",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/354260/images/16241_n.jpg",biography:"Graduated in Pharmacy from the Federal University of Ceará with the modality in Industrial Pharmacy, Specialist in Production and Control of Medicines from the University of São Paulo (USP), Master in Pharmaceuticals and Medicines from the University of São Paulo (USP) and Doctor of Science in the program of Pharmaceuticals and Medicines by the University of São Paulo. Professor at Universidade Paulista (UNIP) in the areas of chemistry, cosmetology and trichology. Assistant Coordinator of the Higher Course in Aesthetic and Cosmetic Technology at Universidade Paulista Campus Chácara Santo Antônio. Experience in the Pharmacy area, with emphasis on Pharmacotechnics, Pharmaceutical Technology, Research and Development of Cosmetics, acting mainly on topics such as cosmetology, antioxidant activity, aesthetics, photoprotection, cyclodextrin and thermal analysis.",institutionString:null,institution:{name:"University of Sao Paulo",country:{name:"Brazil"}}},{id:"334285",title:"Ph.D. Student",name:"Sameer",middleName:"Kumar",surname:"Jagirdar",slug:"sameer-jagirdar",fullName:"Sameer Jagirdar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/334285/images/14691_n.jpg",biography:"I\\'m a graduate student at the center for biosystems science and engineering at the Indian Institute of Science, Bangalore, India. I am interested in studying host-pathogen interactions at the biomaterial interface.",institutionString:null,institution:{name:"Indian Institute of Science Bangalore",country:{name:"India"}}},{id:"329795",title:"Dr.",name:"Mohd Aftab",middleName:"Aftab",surname:"Siddiqui",slug:"mohd-aftab-siddiqui",fullName:"Mohd Aftab Siddiqui",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/329795/images/15648_n.jpg",biography:"Dr. Mohd Aftab Siddiqui is currently working as Assistant Professor in the Faculty of Pharmacy, Integral University, Lucknow for the last 6 years. He has completed his Doctor in Philosophy (Pharmacology) in 2020 from Integral University, Lucknow. He completed his Bachelor in Pharmacy in 2013 and Master in Pharmacy (Pharmacology) in 2015 from Integral University, Lucknow. He is the gold medalist in Bachelor and Master degree. He qualified GPAT -2013, GPAT -2014, and GPAT 2015. His area of research is Pharmacological screening of herbal drugs/ natural products in liver and cardiac diseases. He has guided many M. Pharm. research projects. He has many national and international publications.",institutionString:"Integral University",institution:null},{id:"255360",title:"Dr.",name:"Usama",middleName:null,surname:"Ahmad",slug:"usama-ahmad",fullName:"Usama Ahmad",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/255360/images/system/255360.png",biography:"Dr. Usama Ahmad holds a specialization in Pharmaceutics from Amity University, Lucknow, India. He received his Ph.D. degree from Integral University. Currently, he’s working as an Assistant Professor of Pharmaceutics in the Faculty of Pharmacy, Integral University. From 2013 to 2014 he worked on a research project funded by SERB-DST, Government of India. He has a rich publication record with more than 32 original articles published in reputed journals, 3 edited books, 5 book chapters, and a number of scientific articles published in ‘Ingredients South Asia Magazine’ and ‘QualPharma Magazine’. He is a member of the American Association for Cancer Research, International Association for the Study of Lung Cancer, and the British Society for Nanomedicine. Dr. Ahmad’s research focus is on the development of nanoformulations to facilitate the delivery of drugs that aim to provide practical solutions to current healthcare problems.",institutionString:"Integral University",institution:{name:"Integral University",country:{name:"India"}}},{id:"30568",title:"Prof.",name:"Madhu",middleName:null,surname:"Khullar",slug:"madhu-khullar",fullName:"Madhu Khullar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/30568/images/system/30568.jpg",biography:"Dr. Madhu Khullar is a Professor of Experimental Medicine and Biotechnology at the Post Graduate Institute of Medical Education and Research, Chandigarh, India. She completed her Post Doctorate in hypertension research at the Henry Ford Hospital, Detroit, USA in 1985. She is an editor and reviewer of several international journals, and a fellow and member of several cardiovascular research societies. Dr. Khullar has a keen research interest in genetics of hypertension, and is currently studying pharmacogenetics of hypertension.",institutionString:"Post Graduate Institute of Medical Education and Research",institution:{name:"Post Graduate Institute of Medical Education and Research",country:{name:"India"}}},{id:"223233",title:"Prof.",name:"Xianquan",middleName:null,surname:"Zhan",slug:"xianquan-zhan",fullName:"Xianquan Zhan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/223233/images/system/223233.png",biography:"Xianquan Zhan received his MD and Ph.D. in Preventive Medicine at West China University of Medical Sciences. He received his post-doctoral training in oncology and cancer proteomics at the Central South University, China, and the University of Tennessee Health Science Center (UTHSC), USA. He worked at UTHSC and the Cleveland Clinic in 2001–2012 and achieved the rank of associate professor at UTHSC. Currently, he is a full professor at Central South University and Shandong First Medical University, and an advisor to MS/PhD students and postdoctoral fellows. He is also a fellow of the Royal Society of Medicine and European Association for Predictive Preventive Personalized Medicine (EPMA), a national representative of EPMA, and a member of the American Society of Clinical Oncology (ASCO) and the American Association for the Advancement of Sciences (AAAS). He is also the editor in chief of International Journal of Chronic Diseases & Therapy, an associate editor of EPMA Journal, Frontiers in Endocrinology, and BMC Medical Genomics, and a guest editor of Mass Spectrometry Reviews, Frontiers in Endocrinology, EPMA Journal, and Oxidative Medicine and Cellular Longevity. He has published more than 148 articles, 28 book chapters, 6 books, and 2 US patents in the field of clinical proteomics and biomarkers.",institutionString:"Shandong First Medical University",institution:{name:"Affiliated Hospital of Shandong Academy of Medical Sciences",country:{name:"China"}}},{id:"297507",title:"Dr.",name:"Charles",middleName:"Elias",surname:"Assmann",slug:"charles-assmann",fullName:"Charles Assmann",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/297507/images/system/297507.jpg",biography:"Charles Elias Assmann is a biologist from Federal University of Santa Maria (UFSM, Brazil), who spent some time abroad at the Ludwig-Maximilians-Universität München (LMU, Germany). He has Masters Degree in Biochemistry (UFSM), and is currently a PhD student at Biochemistry at the Department of Biochemistry and Molecular Biology of the UFSM. His areas of expertise include: Biochemistry, Molecular Biology, Enzymology, Genetics and Toxicology. He is currently working on the following subjects: Aluminium toxicity, Neuroinflammation, Oxidative stress and Purinergic system. Since 2011 he has presented more than 80 abstracts in scientific proceedings of national and international meetings. Since 2014, he has published more than 20 peer reviewed papers (including 4 reviews, 3 in Portuguese) and 2 book chapters. He has also been a reviewer of international journals and ad hoc reviewer of scientific committees from Brazilian Universities.",institutionString:"Universidade Federal de Santa Maria",institution:{name:"Universidade Federal de Santa Maria",country:{name:"Brazil"}}},{id:"217850",title:"Dr.",name:"Margarete Dulce",middleName:null,surname:"Bagatini",slug:"margarete-dulce-bagatini",fullName:"Margarete Dulce Bagatini",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/217850/images/system/217850.jpeg",biography:"Dr. Margarete Dulce Bagatini is an associate professor at the Federal University of Fronteira Sul/Brazil. She has a degree in Pharmacy and a PhD in Biological Sciences: Toxicological Biochemistry. She is a member of the UFFS Research Advisory Committee\nand a member of the Biovitta Research Institute. She is currently:\nthe leader of the research group: Biological and Clinical Studies\nin Human Pathologies, professor of postgraduate program in\nBiochemistry at UFSC and postgraduate program in Science and Food Technology at\nUFFS. She has experience in the area of pharmacy and clinical analysis, acting mainly\non the following topics: oxidative stress, the purinergic system and human pathologies, being a reviewer of several international journals and books.",institutionString:"Universidade Federal da Fronteira Sul",institution:{name:"Universidade Federal da Fronteira Sul",country:{name:"Brazil"}}},{id:"226275",title:"Ph.D.",name:"Metin",middleName:null,surname:"Budak",slug:"metin-budak",fullName:"Metin Budak",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226275/images/system/226275.jfif",biography:"Metin Budak, MSc, PhD is an Assistant Professor at Trakya University, Faculty of Medicine. He has been Head of the Molecular Research Lab at Prof. Mirko Tos Ear and Hearing Research Center since 2018. His specializations are biophysics, epigenetics, genetics, and methylation mechanisms. He has published around 25 peer-reviewed papers, 2 book chapters, and 28 abstracts. He is a member of the Clinical Research Ethics Committee and Quantification and Consideration Committee of Medicine Faculty. His research area is the role of methylation during gene transcription, chromatin packages DNA within the cell and DNA repair, replication, recombination, and gene transcription. His research focuses on how the cell overcomes chromatin structure and methylation to allow access to the underlying DNA and enable normal cellular function.",institutionString:"Trakya University",institution:{name:"Trakya University",country:{name:"Turkey"}}},{id:"243049",title:"Dr.",name:"Anca",middleName:null,surname:"Pantea Stoian",slug:"anca-pantea-stoian",fullName:"Anca Pantea Stoian",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/243049/images/system/243049.jpg",biography:"Anca Pantea Stoian is a specialist in diabetes, nutrition, and metabolic diseases as well as health food hygiene. She also has competency in general ultrasonography.\n\nShe is an associate professor in the Diabetes, Nutrition and Metabolic Diseases Department, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania. She has been chief of the Hygiene Department, Faculty of Dentistry, at the same university since 2019. Her interests include micro and macrovascular complications in diabetes and new therapies. Her research activities focus on nutritional intervention in chronic pathology, as well as cardio-renal-metabolic risk assessment, and diabetes in cancer. She is currently engaged in developing new therapies and technological tools for screening, prevention, and patient education in diabetes. \n\nShe is a member of the European Association for the Study of Diabetes, Cardiometabolic Academy, CEDA, Romanian Society of Diabetes, Nutrition and Metabolic Diseases, Romanian Diabetes Federation, and Association for Renal Metabolic and Nutrition studies. She has authored or co-authored 160 papers in national and international peer-reviewed journals.",institutionString:null,institution:{name:"Carol Davila University of Medicine and Pharmacy",country:{name:"Romania"}}},{id:"279792",title:"Dr.",name:"João",middleName:null,surname:"Cotas",slug:"joao-cotas",fullName:"João Cotas",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/279792/images/system/279792.jpg",biography:"Graduate and master in Biology from the University of Coimbra.\n\nI am a research fellow at the Macroalgae Laboratory Unit, in the MARE-UC – Marine and Environmental Sciences Centre of the University of Coimbra. My principal function is the collection, extraction and purification of macroalgae compounds, chemical and bioactive characterization of the compounds and algae extracts and development of new methodologies in marine biotechnology area. \nI am associated in two projects: one consists on discovery of natural compounds for oncobiology. The other project is the about the natural compounds/products for agricultural area.\n\nPublications:\nCotas, J.; Figueirinha, A.; Pereira, L.; Batista, T. 2018. An analysis of the effects of salinity on Fucus ceranoides (Ochrophyta, Phaeophyceae), in the Mondego River (Portugal). Journal of Oceanology and Limnology. in press. DOI: 10.1007/s00343-019-8111-3",institutionString:"Faculty of Sciences and Technology of University of Coimbra",institution:null},{id:"279788",title:"Dr.",name:"Leonel",middleName:null,surname:"Pereira",slug:"leonel-pereira",fullName:"Leonel Pereira",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/279788/images/system/279788.jpg",biography:"Leonel Pereira has an undergraduate degree in Biology, a Ph.D. in Biology (specialty in Cell Biology), and a Habilitation degree in Biosciences (specialization in Biotechnology) from the Faculty of Science and Technology, University of Coimbra, Portugal, where he is currently a professor. In addition to teaching at this university, he is an integrated researcher at the Marine and Environmental Sciences Center (MARE), Portugal. His interests include marine biodiversity (algae), marine biotechnology (algae bioactive compounds), and marine ecology (environmental assessment). Since 2008, he has been the author and editor of the electronic publication MACOI – Portuguese Seaweeds Website (www.seaweeds.uc.pt). He is also a member of the editorial boards of several scientific journals. Dr. Pereira has edited or authored more than 20 books, 100 journal articles, and 45 book chapters. He has given more than 100 lectures and oral communications at various national and international scientific events. He is the coordinator of several national and international research projects. In 1998, he received the Francisco de Holanda Award (Honorable Mention) and, more recently, the Mar Rei D. Carlos award (18th edition). He is also a winner of the 2016 CHOICE Award for an outstanding academic title for his book Edible Seaweeds of the World. In 2020, Dr. Pereira received an Honorable Mention for the Impact of International Publications from the Web of Science",institutionString:"University of Coimbra",institution:{name:"University of Coimbra",country:{name:"Portugal"}}},{id:"61946",title:"Dr.",name:"Carol",middleName:null,surname:"Bernstein",slug:"carol-bernstein",fullName:"Carol Bernstein",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/61946/images/system/61946.jpg",biography:"Carol Bernstein received her PhD in Genetics from the University of California (Davis). She was a faculty member at the University of Arizona College of Medicine for 43 years, retiring in 2011. Her research interests focus on DNA damage and its underlying role in sex, aging and in the early steps of initiation and progression to cancer. In her research, she had used organisms including bacteriophage T4, Neurospora crassa, Schizosaccharomyces pombe and mice, as well as human cells and tissues. She authored or co-authored more than 140 scientific publications, including articles in major peer reviewed journals, book chapters, invited reviews and one book.",institutionString:"University of Arizona",institution:{name:"University of Arizona",country:{name:"United States of America"}}},{id:"182258",title:"Dr.",name:"Ademar",middleName:"Pereira",surname:"Serra",slug:"ademar-serra",fullName:"Ademar Serra",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/182258/images/system/182258.jpeg",biography:"Dr. Serra studied Agronomy on Universidade Federal de Mato Grosso do Sul (UFMS) (2005). He received master degree in Agronomy, Crop Science (Soil fertility and plant nutrition) (2007) by Universidade Federal da Grande Dourados (UFGD), and PhD in agronomy (Soil fertility and plant nutrition) (2011) from Universidade Federal da Grande Dourados / Escola Superior de Agricultura Luiz de Queiroz (UFGD/ESALQ-USP). Dr. Serra is currently working at Brazilian Agricultural Research Corporation (EMBRAPA). His research focus is on mineral nutrition of plants, crop science and soil science. Dr. Serra\\'s current projects are soil organic matter, soil phosphorus fractions, compositional nutrient diagnosis (CND) and isometric log ratio (ilr) transformation in compositional data analysis.",institutionString:"Brazilian Agricultural Research Corporation",institution:{name:"Brazilian Agricultural Research Corporation",country:{name:"Brazil"}}}]}},subseries:{item:{id:"10",type:"subseries",title:"Animal Physiology",keywords:"Physiology, Comparative, Evolution, Biomolecules, Organ, Homeostasis, Anatomy, Pathology, Medical, Cell Division, Cell Signaling, Cell Growth, Cell Metabolism, Endocrine, Neuroscience, Cardiovascular, Development, Aging, Development",scope:"Physiology, the scientific study of functions and mechanisms of living systems, is an essential area of research in its own right, but also in relation to medicine and health sciences. The scope of this topic will range from molecular, biochemical, cellular, and physiological processes in all animal species. 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She obtained a BSc from the University of Derby, England, a master’s degree from Technische Universität München, Germany, and a Ph.D. from the University of Nottingham. She undertook a post-doctoral research fellowship in the School of Medicine before accepting tenure in Veterinary Medicine and Science. Dr. Rutland also obtained an MMedSci (Medical Education) and a Postgraduate Certificate in Higher Education (PGCHE). She is the author of more than sixty peer-reviewed journal articles, twelve books/book chapters, and more than 100 research abstracts in cardiovascular biology and oncology. She is a board member of the European Association of Veterinary Anatomists, Fellow of the Anatomical Society, and Senior Fellow of the Higher Education Academy. Dr. Rutland has also written popular science books for the public. https://orcid.org/0000-0002-2009-4898. www.nottingham.ac.uk/vet/people/catrin.rutland",institutionString:null,institution:{name:"University of Nottingham",institutionURL:null,country:{name:"United Kingdom"}}},editorTwo:null,editorThree:null,series:{id:"10",title:"Physiology",doi:"10.5772/intechopen.72796",issn:"2631-8261"},editorialBoard:[{id:"306970",title:"Mr.",name:"Amin",middleName:null,surname:"Tamadon",slug:"amin-tamadon",fullName:"Amin Tamadon",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002oHR5wQAG/Profile_Picture_1623910304139",institutionString:null,institution:{name:"Bushehr University of Medical Sciences",institutionURL:null,country:{name:"Iran"}}},{id:"251314",title:"Dr.",name:"Juan Carlos",middleName:null,surname:"Gardón",slug:"juan-carlos-gardon",fullName:"Juan Carlos 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