Decision structuredness [6].
\\n\\n
IntechOpen Book Series will also publish a program of research-driven Thematic Edited Volumes that focus on specific areas and allow for a more in-depth overview of a particular subject.
\\n\\nIntechOpen Book Series will be launching regularly to offer our authors and editors exciting opportunities to publish their research Open Access. We will begin by relaunching some of our existing Book Series in this innovative book format, and will expand in 2022 into rapidly growing research fields that are driving and advancing society.
\\n\\nLaunching 2021
\\n\\nArtificial Intelligence, ISSN 2633-1403
\\n\\nVeterinary Medicine and Science, ISSN 2632-0517
\\n\\nBiochemistry, ISSN 2632-0983
\\n\\nBiomedical Engineering, ISSN 2631-5343
\\n\\nInfectious Diseases, ISSN 2631-6188
\\n\\nPhysiology (Coming Soon)
\\n\\nDentistry (Coming Soon)
\\n\\nWe invite you to explore our IntechOpen Book Series, find the right publishing program for you and reach your desired audience in record time.
\\n\\nNote: Edited in October 2021
\\n"}]',published:!0,mainMedia:{caption:"",originalUrl:"/media/original/132"}},components:[{type:"htmlEditorComponent",content:'With the desire to make book publishing more relevant for the digital age and offer innovative Open Access publishing options, we are thrilled to announce the launch of our new publishing format: IntechOpen Book Series.
\n\nDesigned to cover fast-moving research fields in rapidly expanding areas, our Book Series feature a Topic structure allowing us to present the most relevant sub-disciplines. Book Series are headed by Series Editors, and a team of Topic Editors supported by international Editorial Board members. Topics are always open for submissions, with an Annual Volume published each calendar year.
\n\nAfter a robust peer-review process, accepted works are published quickly, thanks to Online First, ensuring research is made available to the scientific community without delay.
\n\nOur innovative Book Series format brings you:
\n\nIntechOpen Book Series will also publish a program of research-driven Thematic Edited Volumes that focus on specific areas and allow for a more in-depth overview of a particular subject.
\n\nIntechOpen Book Series will be launching regularly to offer our authors and editors exciting opportunities to publish their research Open Access. We will begin by relaunching some of our existing Book Series in this innovative book format, and will expand in 2022 into rapidly growing research fields that are driving and advancing society.
\n\nLaunching 2021
\n\nArtificial Intelligence, ISSN 2633-1403
\n\nVeterinary Medicine and Science, ISSN 2632-0517
\n\nBiochemistry, ISSN 2632-0983
\n\nBiomedical Engineering, ISSN 2631-5343
\n\nInfectious Diseases, ISSN 2631-6188
\n\nPhysiology (Coming Soon)
\n\nDentistry (Coming Soon)
\n\nWe invite you to explore our IntechOpen Book Series, find the right publishing program for you and reach your desired audience in record time.
\n\nNote: Edited in October 2021
\n'}],latestNews:[{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"},{slug:"introducing-intechopen-book-series-a-new-publishing-format-for-oa-books-20210915",title:"Introducing IntechOpen Book Series - A New Publishing Format for OA Books"}]},book:{item:{type:"book",id:"6692",leadTitle:null,fullTitle:"Medical and Biological Image Analysis",title:"Medical and Biological Image Analysis",subtitle:null,reviewType:"peer-reviewed",abstract:"This book deals with medical image analysis methods. In particular, it contains two significant chapters on image segmentation as well as some selected examples of the application of image analysis and processing methods. Despite the significant development of information technology methods used in modern image analysis and processing algorithms, the segmentation process remains open. This is mainly due to intra-patient variability and/or scene diversity. Segmentation is equally difficult in the case of ultrasound imaging and depends on the location of the probe or the contact force. Regardless of the imaging method, segmentation must be tailored for a specific application in almost every case. These types of application areas for various imaging methods are included in this book.",isbn:"978-1-78923-331-5",printIsbn:"978-1-78923-330-8",pdfIsbn:"978-1-83881-648-3",doi:"10.5772/intechopen.72065",price:119,priceEur:129,priceUsd:155,slug:"medical-and-biological-image-analysis",numberOfPages:134,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"e75f234a0fc1988d9816a94e4c724deb",bookSignature:"Robert Koprowski",publishedDate:"July 4th 2018",coverURL:"https://cdn.intechopen.com/books/images_new/6692.jpg",numberOfDownloads:10105,numberOfWosCitations:17,numberOfCrossrefCitations:28,numberOfCrossrefCitationsByBook:0,numberOfDimensionsCitations:46,numberOfDimensionsCitationsByBook:1,hasAltmetrics:1,numberOfTotalCitations:91,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"November 6th 2017",dateEndSecondStepPublish:"November 27th 2017",dateEndThirdStepPublish:"January 26th 2018",dateEndFourthStepPublish:"April 16th 2018",dateEndFifthStepPublish:"June 15th 2018",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6,7",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"50150",title:"Prof.",name:"Robert",middleName:null,surname:"Koprowski",slug:"robert-koprowski",fullName:"Robert Koprowski",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYTYNQA4/Profile_Picture_1630478535317",biography:"Robert Koprowski, MD (1997), PhD (2003), Habilitation (2015), is an employee of the University of Silesia, Poland, Institute of Computer Science, Department of Biomedical Computer Systems. For 20 years, he has studied the analysis and processing of biomedical images, emphasizing the full automation of measurement for a large inter-individual variability of patients. Dr. Koprowski has authored more than a hundred research papers with dozens in impact factor (IF) journals and has authored or co-authored six books. Additionally, he is the author of several national and international patents in the field of biomedical devices and imaging. Since 2011, he has been a reviewer of grants and projects (including EU projects) in biomedical engineering.",institutionString:null,position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"2",institution:{name:"University of Silesia",institutionURL:null,country:{name:"Poland"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"696",title:"Medical Imaging",slug:"medical-imaging"}],chapters:[{id:"60741",title:"Image Segmentation",doi:"10.5772/intechopen.76428",slug:"image-segmentation",totalDownloads:1272,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:0,abstract:"Image segmentation is one of the important and useful techniques in medical image processing. As the image segmentation technique results robust and high degree of accuracy, it is very much useful for the analysis of different image modalities, such as computerized tomography (CT) and magnetic resonance imaging (MRI) in the medical field. CT imaging gives more importance than MRI because of its wider availability, inexpensive and sensitiveness. In most cases, CT offers information needed to make decisions during urgent situations.",signatures:"Kumaravel Subramaniam Tamilselvan and Govindasamy\nMurugesan",downloadPdfUrl:"/chapter/pdf-download/60741",previewPdfUrl:"/chapter/pdf-preview/60741",authors:[{id:"232687",title:"Dr.",name:"K.S",surname:"Tamilselvan",slug:"k.s-tamilselvan",fullName:"K.S Tamilselvan"},{id:"245153",title:"Dr.",name:"G",surname:"Murugesan",slug:"g-murugesan",fullName:"G Murugesan"}],corrections:null},{id:"59741",title:"Active Contour Based Segmentation Techniques for Medical Image Analysis",doi:"10.5772/intechopen.74576",slug:"active-contour-based-segmentation-techniques-for-medical-image-analysis",totalDownloads:3470,totalCrossrefCites:25,totalDimensionsCites:43,hasAltmetrics:1,abstract:"Image processing is a technique which is used to derive information from the images. Segmentation is a section of image processing for the separation or segregation of information from the required target region of the image. There are different techniques used for segmentation of pixels of interest from the image. Active contour is one of the active models in segmentation techniques, which makes use of the energy constraints and forces in the image for separation of region of interest. Active contour defines a separate boundary or curvature for the regions of target object for segmentation. The contour depends on various constraints based on which they are classified into different types such as gradient vector flow, balloon and geometric models. Active contour models are used in various image processing applications specifically in medical image processing. In medical imaging, active contours are used in segmentation of regions from different medical images such as brain CT images, MRI images of different organs, cardiac images and different images of regions in the human body. Active contours can also be used in motion tracking and stereo tracking. Thus, the active contour segmentation is used for the separation of pixels of interest for different image processing.",signatures:"R.J. Hemalatha, T.R. Thamizhvani, A. Josephin Arockia Dhivya,\nJosline Elsa Joseph, Bincy Babu and R. Chandrasekaran",downloadPdfUrl:"/chapter/pdf-download/59741",previewPdfUrl:"/chapter/pdf-preview/59741",authors:[{id:"238868",title:"Prof.",name:"Hemalatha",surname:"R.J",slug:"hemalatha-r.j",fullName:"Hemalatha R.J"},{id:"242385",title:"Dr.",name:"Chandrasekaran",surname:"R",slug:"chandrasekaran-r",fullName:"Chandrasekaran R"},{id:"242386",title:"Ms.",name:"Thamizhvani",surname:"T.R",slug:"thamizhvani-t.r",fullName:"Thamizhvani T.R"},{id:"242388",title:"Dr.",name:"Josephin Arockia Dhivya",surname:"A",slug:"josephin-arockia-dhivya-a",fullName:"Josephin Arockia Dhivya A"},{id:"242389",title:"Ms.",name:"Josline Elsa",surname:"Joseph",slug:"josline-elsa-joseph",fullName:"Josline Elsa Joseph"},{id:"242390",title:"Ms.",name:"Bincy",surname:"Babu",slug:"bincy-babu",fullName:"Bincy Babu"}],corrections:null},{id:"60362",title:"Medical and Biological Image Analysis",doi:"10.5772/intechopen.75491",slug:"medical-and-biological-image-analysis",totalDownloads:993,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Today, technology and information communication are deeply embedded in our life. Information is present and used in many forms: electronic documents, audio, videos, photos, etc. Recent advances in technology, particularly in the computer industry and communication, have motivated organisations to replace their traditional manually stored and exchanged records with computer systems and digital documents for secure storage and smooth transmission. Medical and biological image processing is a numerical method and technique for modifying a digital image to improve or extract information. The main stages of image processing are:",signatures:"Abdelkader Moumen",downloadPdfUrl:"/chapter/pdf-download/60362",previewPdfUrl:"/chapter/pdf-preview/60362",authors:[{id:"233918",title:"Dr.",name:"Abdelkader",surname:"Moumen",slug:"abdelkader-moumen",fullName:"Abdelkader Moumen"}],corrections:null},{id:"60853",title:"Bioinformatics Solutions for Image Data Processing",doi:"10.5772/intechopen.76459",slug:"bioinformatics-solutions-for-image-data-processing",totalDownloads:1188,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:0,abstract:"In recent years, the increasing use of medical devices has led to the generation of large amounts of data, including image data. Bioinformatics solutions provide an effective approach for image data processing in order to retrieve information of interest and to integrate several data sources for knowledge extraction; furthermore, images processing techniques support scientists and physicians in diagnosis and therapies. In addition, bioinformatics image analysis may be extended to support several scenarios, for instance, in cyber-security the biometric recognition systems are applied to unlock devices and restricted areas, as well as to access sensitive data. In medicine, computational platforms generate high amount of data from medical devices such as Computed Tomography (CT), and Magnetic Resonance Imaging (MRI); this chapter will survey on bioinformatics solutions and toolkits for medical imaging in order to suggest an overview of techniques and methods that can be applied for the imaging analysis in medicine.",signatures:"Pietro Cinaglia, Luciano Caroprese, Giuseppe Lucio Cascini,\nFrancesco Dattola, Pasquale Iaquinta, Miriam Iusi, Pierangelo Veltri\nand Ester Zumpano",downloadPdfUrl:"/chapter/pdf-download/60853",previewPdfUrl:"/chapter/pdf-preview/60853",authors:[{id:"236617",title:"Prof.",name:"Ester",surname:"Zumpano",slug:"ester-zumpano",fullName:"Ester Zumpano"},{id:"248312",title:"Dr.",name:"Pietro",surname:"Cinaglia",slug:"pietro-cinaglia",fullName:"Pietro Cinaglia"},{id:"248313",title:"Dr.",name:"Luciano",surname:"Caroprese",slug:"luciano-caroprese",fullName:"Luciano Caroprese"},{id:"248316",title:"Prof.",name:"Giueppe Lucio",surname:"Cascini",slug:"giueppe-lucio-cascini",fullName:"Giueppe Lucio Cascini"},{id:"248317",title:"Dr.",name:"Francesco",surname:"Dattola",slug:"francesco-dattola",fullName:"Francesco Dattola"},{id:"248319",title:"Dr.",name:"Pasquale",surname:"Iaquinta",slug:"pasquale-iaquinta",fullName:"Pasquale Iaquinta"},{id:"248320",title:"Dr.",name:"Miriam",surname:"Iusi",slug:"miriam-iusi",fullName:"Miriam Iusi"},{id:"248321",title:"Prof.",name:"Pierangelo",surname:"Veltri",slug:"pierangelo-veltri",fullName:"Pierangelo Veltri"}],corrections:null},{id:"60152",title:"Abnormal Tissue Zone Detection and Average Active Stress Estimation in Patients with LV Dysfunction",doi:"10.5772/intechopen.75202",slug:"abnormal-tissue-zone-detection-and-average-active-stress-estimation-in-patients-with-lv-dysfunction",totalDownloads:977,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:0,abstract:"Detection of regional ventricular dysfunction is a challenging problem. This study presents an efficient method based on ultrasound (US) imaging and finite element (FE) analysis, for detecting akinetic and dyskinetic regions in the left ventricle (LV). The underlying hypothesis is that the contraction of a healthy LV is approximately homogeneous. Therefore, any deviations between the image-based measured deformation and a homogeneous contraction FE model should correspond to a pathological region. The method was first successfully applied to synthetic data simulating an acute ischemia; it demonstrated that the pathological areas were revealed with a higher contrast than those observed directly in the deformation maps. The technique was then applied to a cohort of eight left bundle branch block (LBBB) patients. For this group, the heterogeneities were significantly less pronounced than those revealed for the synthetic cases but the method was still able to identify the abnormal regions of the LV. This study indicated the potential clinical utility of the method by its simplicity in a patient-specific context and its ability to quickly identify various heterogeneities in LV function. Further studies are required to determine the model accuracy in other pathologies and to investigate its robustness to noise and image artifacts.",signatures:"Sareh Behdadfar, Laurent Navarro, Joakim Sundnes, Molly\nMaleckar, Hans Henrik Odland and Stephane Avril",downloadPdfUrl:"/chapter/pdf-download/60152",previewPdfUrl:"/chapter/pdf-preview/60152",authors:[{id:"53776",title:"Dr.",name:"Laurent",surname:"Navarro",slug:"laurent-navarro",fullName:"Laurent Navarro"},{id:"233287",title:"Prof.",name:"Stephane",surname:"Avril",slug:"stephane-avril",fullName:"Stephane Avril"},{id:"243118",title:"Dr.",name:"Sareh",surname:"Behdadfar",slug:"sareh-behdadfar",fullName:"Sareh Behdadfar"},{id:"243119",title:"Dr.",name:"Mary M",surname:"Maleckar",slug:"mary-m-maleckar",fullName:"Mary M Maleckar"},{id:"243120",title:"Dr.",name:"Hans Henrik",surname:"Odland",slug:"hans-henrik-odland",fullName:"Hans Henrik Odland"},{id:"243121",title:"Prof.",name:"Joakim",surname:"Sundnes",slug:"joakim-sundnes",fullName:"Joakim Sundnes"}],corrections:null},{id:"58652",title:"Non-Conventional Radiotherapy for Total Body Irradiation: Antecedents, Current Research and Perspectives",doi:"10.5772/intechopen.73026",slug:"non-conventional-radiotherapy-for-total-body-irradiation-antecedents-current-research-and-perspectiv",totalDownloads:1028,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"In addition to the conventional techniques used in radiotherapy, certain procedures, special-called for the treatment of both some cancer diseases and clinical application are usually required. Such practices typically manifest a technical problem with respect to the equipment used, which requires important adjusts that diverge significantly from the standard implemented in the common treatments. Total body irradiation is one of those special techniques, in which the radiation target is the entire patient body. In a broad sense, the concept covers all radiation processes with photon beam fields more wide than standard field size. Treatment with total body irradiation is usually applied with purpose of providing immunosuppression to prevent rejection in bone marrow transplantation procedure. Diseases such as aplastic anemia and a varied number of leukemia and lymphomas respond favorably to this treatment scheme. Beams of megavoltage photons, such as Cobalt sources and linear accelerators, are used for such purposes. In this chapter, the technique will be studied analyzing its definition and first applications. The chapter includes a description of the main treatment schemes on which it is based, covering the calibration process, ergonomic criteria as well as the main contributions in the clinical research field, opportunity fields and novel research perspectives.",signatures:"Francisco Mesa-Linares",downloadPdfUrl:"/chapter/pdf-download/58652",previewPdfUrl:"/chapter/pdf-preview/58652",authors:[{id:"233671",title:"Dr.",name:"Francisco",surname:"Mesa-Linares",slug:"francisco-mesa-linares",fullName:"Francisco Mesa-Linares"}],corrections:null},{id:"60729",title:"Automatic Image Analysis and Recognition for Ultrasound Diagnosis and Treatment in Cardiac, Obstetrics and Radiology",doi:"10.5772/intechopen.76284",slug:"automatic-image-analysis-and-recognition-for-ultrasound-diagnosis-and-treatment-in-cardiac-obstetric",totalDownloads:1179,totalCrossrefCites:1,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Ultrasound image analysis and recognition techniques for improving workflow in diagnosis and treatment are introduced. Fully automatic techniques for applications of cardiac plane extraction, foetal weight measurement and ultrasound-CT image registration for liver surgery navigation are included. For standard plane extraction in 3D cardiac ultrasound, multiple cardiac landmarks defined in ultrasound cardiac examination guidelines are detected and localized by a Hough-forest-based detector, and by six standard cardiac planes, cardiac diagnosis is extracted following the guideline. For automatic foetal weight measurement, biparietal diameter (BPD), femur length (FL) and abdominal circumference (AC) are estimated by segmenting corresponding organs and regions from foetal ultrasound images. For ultrasound-CT liver image registration, initial alignment is obtained by localizing a corresponding portal vein branch from an intraoperative ultrasound and preoperative CT image pair. Then portal vein regions of the ultrasound-CT image pair are extracted by a machine learning method and are used for image registration.",signatures:"Zisheng Li, Peifei Zhu, Takashi Toyomura and Yoshimi Noguchi",downloadPdfUrl:"/chapter/pdf-download/60729",previewPdfUrl:"/chapter/pdf-preview/60729",authors:[{id:"237293",title:"Ph.D.",name:"Zisheng",surname:"Li",slug:"zisheng-li",fullName:"Zisheng Li"},{id:"246858",title:"Ms.",name:"Peifei",surname:"Zhu",slug:"peifei-zhu",fullName:"Peifei Zhu"},{id:"246859",title:"Mr.",name:"Takashi",surname:"Toyomura",slug:"takashi-toyomura",fullName:"Takashi Toyomura"},{id:"246860",title:"Mr.",name:"Yoshimi",surname:"Noguchi",slug:"yoshimi-noguchi",fullName:"Yoshimi Noguchi"}],corrections:null}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},subseries:{id:"7",series:{id:"7",title:"Biomedical Engineering",issn:"2631-5343",editor:{id:"50150",title:"Prof.",name:"Robert",middleName:null,surname:"Koprowski",slug:"robert-koprowski",fullName:"Robert Koprowski",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYTYNQA4/Profile_Picture_1630478535317",biography:"Robert Koprowski, MD (1997), PhD (2003), Habilitation (2015), is an employee of the University of Silesia, Poland, Institute of Computer Science, Department of Biomedical Computer Systems. 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Jovandaric and Svetlana J. Milenkovic",coverURL:"https://cdn.intechopen.com/books/images_new/9160.jpg",editedByType:"Edited by",editors:[{id:"268043",title:"Dr.",name:"Miljana Z.",surname:"Jovandaric",slug:"miljana-z.-jovandaric",fullName:"Miljana Z. Jovandaric"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"63078",title:"Decision Support Systems",doi:"10.5772/intechopen.79390",slug:"decision-support-systems",body:'\nAs a matter of fact, nowadays, decision-making is more complicated than it was in the past for two governing reasons. Firstly, growing technology and communication systems have spawned a greater number of feasible solution alternatives from which a decision-maker can select. Secondly, the increased level of structural complexity of today’s problems can result in a chain reaction of magnification of costs if an error should occur [1].
\nTurban and Aronson examined what they consider to be the major factors that affect decision-making, and have drawn conclusions regarding current trends and corresponding results/impacts on decision-making (Figure 1) [2].
\nFactors affecting decision-making [
In general, managerial decisions are derived from human judgment which includes deductive reasoning supported by experience, information and knowledge [3]. To compensate the effect of human error, the decision-making process can be partially supplemented by computer aided automation. The final system cannot be fully automated, unless perfectly processed information and an optimum model is provided.
\nDSS is used to model human reasoning and the decision-making process; both are capable of accepting facts from users, processing these facts, and suggesting the solutions that are close to the solutions that are presented by human experts [4]. DSS can considerably support in evaluating different maintenance decisions in order to select the most robust and cost-effective answers in a systematic and transparent way [5].
\nThe growing level of decision support system accomplishment in organizations over the recent decades is strong proof that DSS is a viable and well accepted managerial tool.
\nOver the past fifty-plus years, the field of Information Systems (IS) has undergone a considerable progression of growth. Each expansion has built on its predecessors and supplemented them in the process [6].
\nBefore 1965, it was extremely expensive to build a large-scale information system. Around this time, the establishment of the IBM System 360 and other more powerful processor systems made it more practical and cost-effective to build management information systems (MIS) in large corporations. The pre-specified reports (e.g., budget, cumulative cost and progress statements) output from MIS are data-oriented and restrict decision-makers to gathering the necessary information for making choices, but do not supply a framework to model decision problems. At that point, it was recognized that technological support for decision-making must facilitate ad hoc (problem-specific) recovery of data and managerial control over model manipulation. Decision-makers did not wish to be locked into systems they could not control [7].
\nIn the late 1960s, model-oriented DSS or management decision systems became practical. Two DSS pioneers, Peter Keen and Charles Stabell, stated the concept of decision support which was extracted from the theoretical studies of organizational decision-making during the late 1950s and early 1960s and the technical work on interactive computer systems that mostly carried out in the 1960s [8].
\nIn 1961, Michael S. Scott Morton published “Management Decision Systems: Computer-Based Support for Decision Making.” Later, in 1968–1969, he studied the effect of computers and analytical models in critical decision-making. His research played a “key role in launching the DSS movement” [9].
\nIn 1980, Steven Alter published an important book titled “Decision Support Systems: Current Practice and Continuing Challenge.” His research founded a structure for identifying management DSS [10].
\nBonczek et al. established a theory based on knowledge-based DSS [11]. Their research presented how Artificial Intelligence and Expert System technologies were applicable to developing DSS. They also introduced four essential “aspects” or components of all DSS [12], these are:
A Language System (LS) which includes all the recognizable messages.
A Presentation System (PS) for all messages emitted by DSS.
A Knowledge System (KS) addressing all the imbedded knowledge in a DSS.
A Problem-Processing System (PPS) that tries to diagnose and solve problems.
In the early 1990, business intelligence, data warehousing and On-Line Analytical Processing (OLAP) software began expanding the potential of DSS [10]. Around 1997, the data warehouse became the cornerstone of an integrated knowledge environment that granted a higher level of information sharing, facilitating faster and better decision-making [13].
\nDecision support systems have experienced a noticeable growth in scholarly attention over the past two decades. In according to Google Scholar (October 2007), the rate has increased from less than three publications per week in 1980 to over 20 publications per day twenty-five years later [14]. The Internet and Web have also accelerated developments in decision support and have provided a new way of capturing and documenting the development of knowledge in this research area [10].
\nAccording to Mora et al., the decision maker employs computer technology to: (a) organize the information into problem factors, (b) attach all the attributes to a model, (c) use the framework/model to simulate alternatives, and (d) select the best course of action [15]. The outcomes are reported as parameter conditions, experimental forecasts, and/or recommended actions. A typical architecture of DSS provided by Mora et al. is shown in Figure 2 [15].
\nTypical architecture of decision support system (Mora et al., [
Defining standard characteristics of DSS is not viable but the major features that distinguish DSS from other previously established systems can be summarized from Turban and Aronson as follows [2]:
DSS assists decision makers in semi-structured and unstructured problems (which cannot be solved by standard procedural methods or tools), employing human judgment and computers.
It covers a vast spectrum of managerial levels, from top executive to line managers.
Support is provided to both individuals and groups. Less structured situations often require the intervention of several individuals from different divisions and organizational levels or sometimes even from different organizations.
DSS facilitates several interdependent and/or sequential decisions that may be made once, several times, or repeatedly.
DSS carries out all parts of the decision-making process: intelligence, design, choice and implementation.
It covers a variety of decision analysis tools.
DSS is adaptive and flexible, and so users can add, change, delete, or reorganize basic elements.
DSS should be user friendly and have strong graphical interfaces.
DSS tries to improve the effectiveness of decision-making (appropriateness and quality) rather than its efficiency (the cost of decision-making).
DSS attempts to support the decision makers not to replace them. Therefore they will have control over all levels of the process.
End users should be able to build (and modify) simple systems. Complicated systems can be constructed with assistance from information system (IS) experts.
A DSS generally employs models for analysing problems since modeling enables experimenting with different strategies under different configurations.
DSS should be able to supply access to a variety of data sources and formats.
A DSS can be integrated with other systems and/or applications, and it can be distributed through networking and web technologies.
Figure 3 demonstrates an extension of an ideal set of DSS characteristics; based on the work of Turban and Aronson [2].
\nThe desirable characteristics and capabilities of DSS.
Lemass also emphasizes that a DSS should improve both the effectiveness and efficiency of decision-making [1]. Effectiveness is the degree to which identified goals are achieved, whilst efficiency is a measure of the application of resources to attain the goals. The effectiveness and efficiency of a DSS can be measured by its ability to enable decision-makers to:
define difficult problems earlier;
rapidly identify viable solutions;
equitably compare the consequences of each solution;
stylize an interface for displaying problem-specific (ad hoc) data collection and results presentation (e.g., tables, forms, graphics, etc.); and
run sensitivity analyses to check model assumptions and hence help to defend proposed solutions more convincingly.
Traditionally, a decision is defined as being a choice: a choice about a course of action [16], the choice of a strategy for action [17], a choice leading to a certain desired objective [18]. It can be clearly understood that decision-making as a non-random activity concluding in the selection of one course of action among multiple strategies and DSS is a prevailing system that can ease this process [6].
\nSimon stated that the process of making the decision includes three basic phases: intelligence, design, and choice [19]. Turban described how implementation, is also required over and above a “paper” solution, as the fourth phase, in order to solve the original problem [2].
\nThe intelligence phase, or problem identification, involves gaining awareness that inconsistencies exist between the current state of a situation and the desired circumstances. At this level the decision maker tries to diagnose the problems that need to be addressed and/or opportunities that need to be tracked [20].
\nIn the design phase, a decision maker attempts to generate alternatives, and analyses the options to provide knowledge about their relevant implications. During this phase, the decision maker may find that supplementary knowledge is required. This leads to a return to the intelligence stage to clarify the problems before continuing with the design activity [6].
\nDuring the choice phase, the decision maker selects one of the proposed alternatives that have been explored in the design phase. The outcome depends on the nature of the decision context and the decision maker’s own traits and idiosyncrasies. It may be that none of the alternatives are satisfying (return to the design phase), that several competing alternatives gain high scores, or that the state of the context has changed dramatically after analysis of alternatives (return to the intelligence phase). However, one option must be chosen for implementation [21].
\nThe fourth and final step is implementation. This phase includes a set of chosen solutions that need to be approved by stakeholders and put into action over time [20]. This requires cautious planning and sensitivity to those involved in the process and/or those affected by it. The resolution must then be monitored to guarantee that the problem has been corrected. If the problem has been rectified, then the decision-making procedure is finalized [22]. Generally, the outcome of successful implementation is solving the real problem while any failure results in returning to a former phase of the process [2].
\nThere is a variety of decision types which can be classified based on specific factors. An appreciation of decision types can assist decision makers understand what knowledge and knowledge manipulation features would be required in decision support system [6]. The level of “programmability” or structuredness is a helpful aspect for understanding and classifying decisions. Simon argued that decisions could be placed along a spectrum from highly structured to completely unstructured [23]. Decisions may also be further classified as single-stage and multiple-stage, with either risk, certainty or uncertainty of outcome.
\nStructured decisions are made when well-known procedures can be readily applied to all the phases of decision-making to provide standard solutions for repetitive problems. They are characterized by definite decision criteria, a limited number of precise alternatives whose consequences can be worked out without any complexity [24].
\nA semi-structured decision is made when some, but not all, of the phases of decision-making are structured. While some standard solution procedures may be applicable, human judgment is also called upon to develop decisions which tend to be adaptive in nature [1].
\nWhen none of the phases of decision-making are structured, the resulting decisions are classified as unstructured. Lack of clear decision criterion and the difficulty in identifying a finite set of alternatives and high levels of uncertainty concerning the consequences of the known alternatives at most of the decision levels, are all symptoms of this unstructuredness [25].
\nSemi-structured and unstructured decisions are made when problems are ill-defined (ill-structured). Srinivasan et al. notes that most real-world problems fall towards the unstructured end of this spectrum [20]. Table 1 demonstrates the characteristics of structured and unstructured decisions.
\nStructured decisions | \nUnstructured decisions | \n
---|---|
Routine, repetitive | \nUnexpected, infrequent | \n
Established and stable context | \nEmergent and turbulent contexts | \n
Alternatives clear | \nAlternatives unclear | \n
Implications of alternatives straightforward | \nImplications of alternatives indeterminate | \n
Criteria for choosing well defined | \nCriteria for choosing ambiguous | \n
Specific knowledge needs known | \nSpecific knowledge needs unknown | \n
Needed knowledge readily available | \nNeeded knowledge unavailable | \n
Result from specialized strategies (i.e., procedures that explicitly pre-specify full set of steps to follow in order to reach decisions) | \nResult from general strategies (e.g., analogy, lateral thinking, brainstorming, synthesis used in the course of reaching decisions) | \n
Reliance on tradition | \nReliance on exploration, creativity, insight, ingenuity | \n
Decision structuredness [6].
Engineering or management decisions are generally made through available data and information that are mostly vague, imprecise, and uncertain by nature [26]. The decision-making process in bridge remediation is one of these ill-structured occasions, which usually need a rigorous approach which applies explicit subject domain knowledge to ill-structured (adaptive) problems in order to reformulate them as structured problems. Multi-attribute decision-making (MADM) is an efficient tool for dealing with uncertainties.
\nA standard feature of multi-attribute decision-making methodology is the decision matrix with m criteria and n alternative as illustrated in Figure 4. In the matrix C1,…,Cm and A1,..,An indicate the criteria and alternatives respectively: each row belongs to a criterion and each column describes the performance of an alternative. The score aij describes the performance of alternative Aj against criterion Ci. It has been conventionally assumed that a higher score value means a better performance [27].
\nThe decision matrix.
As shown in Figure 4, weights W1,…,Wm are assigned to the criteria. Weight Wi reflects the relative importance of criteria Ci to the decision, and is assumed to be positive. The weights of the criteria are typically defined on subjective basis. The values X1,…,Xn related to the alternatives in the decision matrix are used in the Multi-Attribute Utility Theory (MAUT) methods. Generally, higher ranking value represents a higher performance of the alternative, so the item with the highest ranking is the best action item [27].
\nIn addition to some monetary based and elementary methods, the two main families in the multi-attribute decision-making methods are those founded on the MAUT and Outranking Methods.
\nThese elementary approaches are characterized by their simplicity and their independence to computational support. They are suitable for problems with a single decision maker, limited alternatives and criteria which can rarely occur in engineering decision-making [28]. Maximin and Maximax methods, Pros and Cons analysis, Conjunctive and Disjunctive methods and the Lexicographic method are all in this category [29].
\nThe Maximin method’s strategy is to avoid the worst possible performance, maximizing the minimal performing criterion. The alternative, for which the score of its weakest criterion is the highest, is preferred. For example, a weight of one is given to the criterion which is least best achieved by that choice and a weight of zero to all other criteria. The strategy with the maximum minimum score will be the optimum choice. In contrast to the Maximin method, The Maximax method selects an alternative by its best attribute rather than its worst. This method is particularly useful when the alternatives can be specialized in use based upon one attribute and decision maker has no prior requirement as to which attribute this is [30].
\nPros and Cons analysis is a qualitative comparison method in which positive and negative aspect of each alternative are assessed and compared. It is easy to implement since no mathematical skill is required [29].
\nThe conjunctive and disjunctive methods are non-compensatory screening methods. They do not need criteria to be estimated in commensurate units. These methods require satisfactory rather than best performance in each attribute, i.e., if an action item passes the screening, it is adequate [31].
\nIn Conjunctive method, an alternative must meet a minimal threshold for all attributes while in disjunctive method; the alternative should exceed the given threshold for at least one attribute. Any option that does not meet the rules is deleted from the further consideration [28].
\nDecision trees provide a useful schematic representation of decision and outcome events, provided the number of courses of action, ai, and the number of possible outcomes, Oij, not large. Decision trees are most useful in simple situations where chance events are dependent on the courses of action considered, making the chance events (states of nature) synonymous with outcomes [25].
\nSquare nodes correspond to decision events. Possible courses of action are represented by action lines which link decision events and outcome (chance) events. Circular nodes differentiate the outcome events from the decision events in order to underline that the decision-maker does not have control when chance or Nature determines an outcome [1].
\nThe outcomes for each alternative, originates from the chance nodes and terminate in a partitioned payoff/expected value node. The expected value for each course of action is achieved by summing the expected values of each branch associated with the action [25].
\nA decision tree representation of a problem is shown below as an example. Three strategies (courses of action) are investigated (See Figure 5):
\nA decision tree for selecting the best remediation strategy of a bridge.
a1: replace the distressed bridge section (it would soon be unsafe)
\na2: rehabilitate the bridge (repair costs will not be prohibitive)
\na3: do nothing (the symptoms are more superficial than structural)
\nThe estimated costs of replacement and rehabilitation are $6.3 M and $1.1 M respectively. If the road section is replaced, it is assumed that no further capital costs will be incurred. If the road is rehabilitated and repairs are not satisfactory, an additional $6.3 M replacement cost will result. If no action is taken and the road consequently requires major repairs or becomes totally unserviceable, respective costs of $6.3 M and $18 M will apply (Lemass [1]).
\nIn this example, states of nature are the same as possible outcomes. The outcomes and associated negative payoffs (costs in millions of dollars) can be considered as follows:
\nPayoff | \n||
S1 = O11: | \nthe bridge section is successfully replaced | \nu11 = − $ 6.3 | \n
S2 = O22: | \nthe repairs are satisfactory | \nu22 = − $ 1.1 | \n
S3 = O23: | \nthe repairs are unsatisfactory | \nu23 = − $ 7.4 | \n
S4 = O34: | \nthe bridge section fails, becoming unserviceable | \nu34 = − $ 18.0 | \n
S5 = O35: | \nthe bridge section requires major repairs | \nu35 = − $ 6.3 | \n
S6 = O36: | \nthe bridge section remains satisfactory | \nu36 = − $ 0.0 | \n
The expected value (cost) of action a2 is the lowest, based on the probability (likelihood of occurrence) assigned for each outcome, pij and this course of action can be followed [9].
\nIn lexicographic analysis of problems, a chronological elimination process is continued until either a single solution is found or all the problems are solved. In this method criteria are first rank-ordered in terms of importance. The alternative with the best performance score on the most important criterion is selected. If there are ties related to this attribute, the performance of the joined option on the next most important factor will be compared until the unique alternative is chosen [31].
\nThe concept of cost–benefit analysis (CBA) originated in the United States in the 1930s where it was used to find a solution to problems of water provision. This method is used to estimate all the costs and benefits associated with a particular project which is usually defined in money terms, in order to weigh up whether a project will bring a net benefit to the public and to be able to compare the possible options for limited resources. It is one of the most comprehensive and at the same time the most difficult technique for decision-making [32].
\nAccording to Kuik et al. the application of CBA in an integrated assessment causes the following concerns [33]:
First, CBA measures costs and benefits on the basis of subjective preferences given objective resource constraints and technological possibilities and should probably be evaluated on a case−by−case basis as an open question.
Second, certain costs and benefits which are in the social and environmental domains might be difficult to quantify in monetary terms.
MAUT is based upon the use of utility functions. Utility functions are employed to quantify the preference of the decision-maker by allocating a numerical index to different degrees of satisfaction as the attribute under consideration takes values between the most and least defined limits [34]. They are considered a compliant tool of representing how much an attribute (or a measure) satisfies the decision-maker objectives to transform the raw performance values of the alternatives against diverse criteria, both factual (quantitative) and judgmental (qualitative), to a general dimensionless scale [35]. They represent a means to translate attributes units into utility units. Utility functions can be specified in terms of a graph, table or mathematical expression. Mathematical expressions of utility functions include: straight-line, logarithmic, or exponential functions [34].
\nThe utility values are estimated by normalizing the output of the simulation tests. Normalization of performance measures is conducted utilizing the minimum and maximum limits that are obtained from the simulation. Moreover, they are commonly checked against the outputs and replaced if there are values beyond the limits. The utility functions can be monotonic in a way that the least desirable scenario corresponds to the lowest utility [U(xi) =0] while the most desirable scenario matches with the highest utility [U(xi) =1.0], the interval [0,100] can also be used for this purpose [34].
\nSimple Multi Attribute Rating Technique (SMART) is a method that used to determine the weights of the attributes. This method was initially developed by Edwards [50] and is based on direct numerical ratings that are aggregated additively. There are many derivates of SMART, also including non-additive methods. In a basic format of SMART, there is a rank-ordering of action items for each criterion setting the worst to zero and the best to 100 and interpolating between [27]. By filtering the performance values with associated weights for all criteria a utility value for each option is estimated [36].
\nSMART is independent of the action items/alternatives. The advantage of this approach is that the assessments are not relative; hence shifting the number of options will not change the final outcomes. If new alternatives are likely to be added, and the action items are compliant to a rating model, then SMART can be a better option [37].
\nOne of the limitations of this technique is that it disregards the interrelationships between parameters. However, SMART is a valuable technique since it is uncomplicated, easy and quick which is quite important for decision makers. In SMART, changing the number of alternatives will not change the decision scores of the original alternatives and this is useful when new alternatives are added [37]. He also argued that using SMART in performance measures can be a better alternative than other methods.
\nAHP is a multi-attribute decision-making technique which belongs to the class of methods known as “additive weighting methods” [28]. The AHP was suggested by Saaty and uses an objective function to aggregate various features of a decision where the main goal is to select the decision alternative that has the maximum value of the objective function [38]. The AHP is based on four clearly defined axioms (Saaty [39]). Similar to MAU/VT and SMART, the AHP is classified as a compensatory technique, where attributes/criteria with low scores are compensated by higher scores on other attributes/criteria, but contrasting the utilitarian models, the AHP employs pair wise comparisons of criteria rather than value functions or utility where all criteria are compared and the end results accumulated into a decision-making matrix [40].
\nThe process of AHP includes three phases: decomposition, comparative judgments, and synthesis of priority. Through the AHP process, problems are decomposed into a hierarchical structure, and both quantitative and qualitative information can be used to develop ratio scales between the decision elements at each level using pair wise comparisons. The top level of hierarchy corresponds to overall objectives and the lower levels criteria, sub-criteria, and alternatives. Users are asked to set up a comparison matrix (with comparative judgments) by comparing pairs of criteria or sub-criteria. A scale of quantities -ranging from 1 (indifference) to 9 (extreme preference) is used to identify the users priorities. Eventually, each matrix is then solved by an eigenvector technique for measuring the performance [41].
\nThe comparisons are normally shown in a comparative matrix A, which must be transitive such that if, i > j and j > k then i > k where i, j, and k are action items; for all j > k > i and reciprocal, \n
Through the AHP process, decision-makers’ inconsistency can be calculated via consistency index (CI) to find out whether decisions break the transitivity, and to what extent. A threshold value of 0.10 is acceptable, but if it exceeds then the CI is calculated by using the consistency ratio CR = CI/RI where RI is the ratio index. CI is defined as \n
N | \n1 | \n2 | \n3 | \n4 | \n5 | \n6 | \n7 | \n8 | \n9 | \n10 | \n
---|---|---|---|---|---|---|---|---|---|---|
R1 | \n0 | \n0 | \n0.58 | \n0.9 | \n1.12 | \n1.24 | \n1.32 | \n1.41 | \n1.45 | \n1.49 | \n
Random inconsistency index, adapted from Ishizaka [44].
The advantages of the AHP method are that it demonstrates a systematic approach (through a hierarchy) and it has an objectivity and reliability for estimating weighting factors for criteria [45]. It can also provide a well-tested method which allows analysts to embrace multiple, conflicting, non-monetary attributes into their decision-making.
\nOn the other hand, the disadvantages are that the calculation of a pair-wise comparison matrix for each attribute is quite complicated and as the number of criteria and/or alternatives increases, the complexity of the calculations increases considerably. Moreover if a new alternative is added after finishing an evaluation calculation, it is very troublesome because all the calculation processes have to be restarted again [46].
\nThe limitations of AHP are of a more theoretical nature, and have been the subject of some debate in the technical literature. Many analysts have pointed out that, the attribute weighting questions must be answered with respect to the average performance levels of the alternatives. Others have noted the possibility for ranking reversal among remaining alternatives after one is deleted from consideration. Finally, some theorists go so far as to state that as currently practiced, “the rankings of (AHP) are arbitrary.” Defenders of AHP, such as Saaty himself, answered that rank reversal is not a fault because real-world decision-making shows this characteristic as well [47].
\nThe most important outranking methods assume data availability roughly similar to what required for the MAUT methods. Fundamental problems with most MAUT and MAUT-related methods are handling uncertain or fuzzy information and dealing with information stated in other than ratio or interval scale. In some conditions, instead of quantitative measures descriptive expressions are frequently faced [48]. The outranking method acts as one alternative for approaching complex choice problems with multiple criteria and multiple participants. Outranking shows the degree of domination of one alternative over another and facilitates the employment of incomplete value information and, for example, judgments on ordinal measurement scale. They provide the (partial) preference ranking of the alternatives, not a principal measure of the preference relation [48]. Here the two most famous categories of the outranking methods, the ELECTRE and the PROMETHEE methods are briefly explained.
\nThe ELECTRE method is a part of MCDA (multi criteria decision-aid). The main aim of the ELECTRE method is to choose alternative that unites two conditions from the preference concordance on many evaluations with the competitor and preference discordance was supervised by many options of the comparison. The starting point is the data of the decision matrix assuming the sum of the weights equals to 1 [49]. As shown in Eq. (1), for an ordered pair of alternatives (Aj, Ak), the concordance index Cjk is the sum of all the weights for those attributes where the overall performance of Aj is least as high as Ak.
The concordance index must lies between 0 and 1.
\nThe calculation of the discordance index djk is more complex. If Aj performs better than Ak on all criteria, the discordance index will be zero. Otherwise, as per Eq. (2):
Therefore for each attribute where Ak outperforms Aj, the ratio is computed between the variance in performance between Ak and Aj and the maximum difference in score on the attribute/criterion concerned between the alternatives. The maximum of these ratios (must be between 0 and 1) is the discordance index [27].
\nThis method determines a partial raking on the alternatives. The set of all options that outrank at least one other alternative and are themselves not outranked.
\nThis method was introduced by Brans and Vincke [47], Brans et al. [17], and Edwards [50]. The scores of the decision table need not necessarily be normalized or transformed into a dimensionless scale. Higher score value indicates a better performance. It is also assumed that a preference function is associated to each attribute. For this aim, a preference function PFi(Aj, Ak) is defined showing the degree of the preference of option Aj over Ak for criterion Ci:
\n0≤PFi(Aj, Ak) ≤1 and
\nPFi(Aj, Ak) = 0 no indifference pr preference,
\nPFi(Aj, Ak) ≈ 0 weak preference,
\nPFi(Aj, Ak) ≈ 1 strong preference, and
\nPFi(Aj, Ak) = 1 strict preference.
\nIn most realistic cases, Pi is a function of the deviation d = aij-aik, i.e., PFi(Aj, Ak) = PFi(aij-aik), where PFi is a non-decreasing function, PFi(d) = 0 for d ≤ 0 and 0 ≤ PFi(d) < 1 for d > 0. The main benefit of these preferences functions is the simplicity since there are no more than two parameters in each case.
\nAs shown in Eq. (3), multi criteria preference index π (Aj, Ak) of Aj over Ak can then be calculated considering all the attributes:
The value of this index is between 0 and 1, and characterises the global intensity of preference between the couples of choices [27].
\nFor ranking the alternatives, the following outranking flows (Eq. (4) and Eq. (5)) are classified:
\nPositive outranking flow:
Negative outranking flow:
The positive outranking describes how much each option is outranking the other items. The higher \n
The negative outranking flow shows how much each alternative is outranked by the others. The smaller\n
Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) which was firstly proposed by Hwang and Yoon (1981) is one of the mostly used multi-criteria decision-making techniques [45]. The basic concept of TOPSIS is that the selected option should have the shortest distance from the positive ideal solution and the farthest distance from the negative-ideal solution in a geometrical sense. Within the process an index called “similarity index” is defined to the positive-ideal option by combining the proximity to the positive-ideal and the remoteness from the negative solution- ideal option. Then the method selects a solution with the maximum similarity to the positive-ideal solution. The default assumption is that the larger the outcome, the greater the preference for benefit attributes and the less the preference for cost attributes [51]. The idea of TOPSIS can be expressed in a series of steps:
\nStep 1: Identify performance data for n alternatives over m attributes. Raw measurements are normalized by converting raw measures xij into normalized measures rij as follows (please see Eq. (6)):
Step 2: Estimate weighted normalized ratings as per Eq. (7):
Step 3: Obtain the positive-ideal alternative (extreme performance on each criterion) A+.
\nStep 4: Find the negative-ideal alternative (reverse extreme performance on each criterion) A−.
\nStep 5: Create a distance measure for each decisive factor to both positive-ideal (Si+) and negative-ideal (Si−).
\nStep 6: For each option/alternative, find out a ratio Ci + equal to the distance to the negative-ideal divided by the summation of the distance to the positive-ideal and the distance to the negative-ideal (as shown in Eq. (8)):
Step 7: Rank order all the options by maximizing the ratio (specified) in Step 6.
\nSensitivity analysis is the method used to find whether a particular utility or probability is essential in determining the preferred alternative. There are always some uncertainties for the weights of the criteria and the scores of the alternatives against the subjective (judgmental) criteria [52]. As a result an important question is how the final ranking or the ranking values of the alternatives is sensitive to the changes of some input parameters of the decision model [27].
\nThis chapter covers the definition of decision support system, its ideal characteristics and its background history. Different decision analysis methods including elementary methods, multi attribute utility theory and outranking methods have also been introduced and compared.
\nThe mandibular central and lateral incisors have a single conical root. The root dimensions of both incisors vary corresponding to the crown. They are narrow in mesiodistal dimension and wide in labiolingual dimension and taper uniformly on both proximal sides from the CEJ to the apex. The apical end may curve slightly to the distal. Longitudinal root depressions can be seen in both incisors from the mesial and distal views. Multiple comparisons revealed that, among all permanent teeth, mandibular central incisor has the shortest root. Furthermore, in contrary to maxillary incisors, the root of mandibular lateral incisor is longer than that of mandibular central incisor [1]. It has been reported that the average lengths of mandibular central incisor and lateral incisor roots are 12.6 mm (7.7–17.9) and 13.5 (9.4–18.1), respectively [2]. Kim et al. [3] measured the mandibular incisor root lengths using CBCT in Korean population and found that no significant differences in crown and root lengths were noted between the CBCT-based and direct measurements. The R/C ratios were higher for the mandibular lateral incisors (1.4 ± 0.1) than mandibular central incisors (1.3 ± 0.1) [4]. Therefore, crown lengthening may not be possible in the case of traumatic fracture or iatrogenic orthodontic extrusion due to the short root length in these teeth. Variations in root length between males and females have been reported. According to Zorba et al. [5], it was observed that root length was greater in males than in females. Haghanifar et al. [6] found similar results when comparing crown and root lengths between males and females. He found that females had longer crowns while males had longer roots.
Many authors reported that the external crown and root morphology of mandibular central and lateral incisors are similar [2, 7, 8]. Mandibular incisors usually have a single root, which is wider buccolingually than mesiodistally and tapers toward the apex. The lateral incisor root is larger than that of the central incisor in mesiodistal and labiolingual directions [8, 9]. Variation in number of roots has not been reported in literature. However, Loushine et al. [10] have found two rooted mandibular lateral incisors. However, the shape may vary from conical to round in different populations. Sexual variation in the number and shape of roots has not been reported [9]. Mandibular incisor roots are commonly reported to be straight and in rare occasions curved in the apical region. Curvature can be in the mesial, distal, labial, or lingual direction [9].
Orban stated that the shape of the root canal “to a large degree, conforms to the shape of the root. A few canals are round and tapering, but many are elliptical, broad and thin” [11].
The internal anatomy of permanent mandibular incisors does not usually reproduce the simplicity of external anatomy. Its internal anatomy is complicated by the presence of lingual canals, lateral canals, isthmus, and apical deltas [12]. The pulp cavity is the central cavity within a tooth and is entirely enclosed by dentin except at apical foramen. It is divided into coronal portion (pulp chamber) and radicular portion. The pulp chamber is wide and ovoid labiolingually and it tapers incisally. The size of the pulp chamber is not constant throughout life. It decreases in size with aging as a result of secondary dentin deposition [13]. The pulp horn is well developed in this tooth. The root canal systems of these single-rooted teeth often have a single root with a single root canal. However, studies have shown that the root canal anatomy of these teeth is not simple. It may not be single and straight as it appears on the periapical radiograph. Indeed, these teeth have a high prevalence of bifurcation, second canals, lateral canals, and apical deltas which would complicate surgical and nonsurgical endodontic treatment. Mandibular incisor’s anatomy presents a challenge when an endodontic access is made, because of its small size and high prevalence of two canals. The main reason for failure in endodontic treatment of mandibular incisors is the inability to detect the presence of a second canal which can then not be prepared and filled during treatment [14]. In literature, the incidence of mandibular incisor teeth with more than one canal has been reported to range from 11 to 68% [15, 16, 17, 18, 19]. The differences between these morphology studies may be related to variations of examination methods, classification systems, sample sizes, and ethnic background of tooth sources. Many researchers have studied the prevalence of a second canal in mandibular permanent incisors on different populations and showed that the root canal morphology varies with race, sex, and age [20, 21, 22, 23, 24].
Routine clinical radiographs may mislead clinicians to be under an impression that all root canals are round in shape. A high prevalence of oval root canals in human teeth was reported [25, 26].
The pulp canal of the permanent mandibular central incisor is wider buccolingually than mesiodistally [9]. These dimensions are not constant along the root from the orifice till the apex. Oval canals and long oval canals are the most common canal shape seen in the coronal and middle third [27]. As we approach the apex, the canal shape becomes more rounded [28]. This canal shape morphology corresponds to the shape of the root.
The root canal morphology of mandibular central and lateral incisors is very similar. Although they have only one root and a high prevalence of Type 1 root canal morphology, surgical and nonsurgical root canal treatment may fail in these teeth if there is a lack of awareness in their internal anatomy which is complicated by the presence of the lingual canal, bifurcation, lateral anatomy, and isthmus [17, 29]. The morphological characteristics of the root canal system were studied using a number of techniques [18, 27, 30]. The prevalence of a second canal in mandibular permanent incisors is different between populations. Vertucci [18] reported that the incidence of the presence of a second canal was 25.7% among American population, whereas the incidence in Chinese population for the mandibular central and lateral incisors was 5.71 and 27.36%, respectively [31], 30% in Saudi population [32], 26.2% in north Jordanian population [33], and 36.25% in North-East Indian population [34]. In Iranian population, the incidence of mandibular central and lateral incisors having two canals was 27.3 and 29.4%, respectively [35]. The highest incidence (63%) of a second canal in mandibular incisors has been reported in a study in Turkish population [19].
Rankine-Wilson and Henry [36] filled the root canals of mandibular anterior teeth with radio-opaque material, sectioned them in a horizontal plane, and exposed radiographs. They reported two canals in 40.5% of mandibular incisors. Later, Vertucci [18] studied the root canal morphology of 300 extracted mandibular anterior teeth using the clearing technique. In 30% of mandibular central incisors and in 25% of mandibular lateral incisors, there was a second canal. On the other hand, higher prevalence of a second canal in Chinese population was reported in lateral mandibular incisors 25.5% compared with 10.9% in central mandibular incisors [37].
Many researches have shown that root canal systems also vary according to gender. In Turkish population, Sert and Bayirli [19] reported the incidence of second canal in central incisors in females (70%) was higher than in males (65%). Also in Turkish population, Arslan et al. [38] found the frequency of mandibular incisors with a second root canal in males (63%) was higher than in females (35%). The differences among both studies may be due to the fact that Sert and Bayirli examined the root canal morphology in vitro, whereas Arslan et al. studied the root canal anatomy in vivo. In Chinese population, Zhengyan et al. [30] found a significant difference between sex. The result of his study showed that 9.4% of the mandibular lateral incisors in males had a second canal, whereas this value was 11.9% in females. Among Iranian population, Haji et al. [39] reported that there was no significant difference between males and females in the incidence of a second canal in mandibular incisors.
It has become clear that teeth have complicated root canal systems rather than simplified canals [40]. Most investigators have shown that the root canal systems for most, if not all, permanent teeth are complex and canals may branch, divide, and rejoin. In addition to the complexity of root canal anatomy, root canal morphology varies from tooth to tooth. Concerning root canal treatment, these variations in root canal morphology of permanent teeth may result in missing root canals, nonsurgical endodontic treatment failure, and a need for surgical procedures. Weine et al. [41] classified root canal systems into four basic types, but Vertucci [18] subsequently classified them into eight configurations. The Vertucci classification may give consideration to the complex reality of canal systems in a way that the Weine et al. system did not.
Weine [42] described each of the canal types as below:
Vertucci [24] classified canal configurations into eight types as described below:
Although mandibular incisors are usually single-rooted teeth, their root canal system cannot be predicted not only between different populations but also between the same population, with respect to the Vertucci’s configuration. Studies reported that Vertucci’s Type I configuration has the highest prevalence among the other Vertucci configurations [43, 44, 45]. When a second canal is present, Vertucci’s Type III configuration is the most common for central and lateral incisors. Scarlatescu [46] found Type III has higher incidence than Type II, of 25 and 6.3% respectively in a Romanian population. de Almeida [47] reported that Vertucci’s Type I and III configurations represented 92% of the sample. Leoni investigated the root canal anatomy of mandibular central (
Lateral canals are accessory canals located in the coronal or middle third of the root, extending horizontally from the main canal to the external surface of the root. Their formation is due to the entrapment of periodontal vessels in Hertwig’s epithelial root sheath or when blood vessels running from the dental sac through the dental papilla persist during calcification [50]. Lateral canals communicate with the periodontal ligament space and this increases risk of spread of periodontal disease into the pulp canal. According to their location, Vertucci classified lateral canals into coronal, middle, apical, or furcation. He observed lower occurrence of canal ramifications in the middle 11.4% and coronal 6.3% thirds compared to the apical 73.5% third [18, 24]. Recent micro-CT studies on root canal morphology of mandibular anterior teeth reported that lateral canals are rare [48, 51]. Miyashita et al. [17] reported that out of mandibular incisors with lateral branches, single lateral branch had the highest prevalence (82.2%) and multiple branches were extremely narrow. Al-Qudah and Awawdeh [33] found that there was an increasing prevalence of lateral canals toward the apical third of the root with approximately 64% occurring in the apical part of the roots. On the other hand, other studies reported that lateral canals were frequently found in the middle of the canal [34, 46]. Clinically, lateral canals are not usually visible in preoperative radiographs, but its presence can be suspected when there is a localized thickening of the periodontal ligament or a lesion on the lateral surface of the root [50]. It is also important to note that lateral canals cannot be instrumented. Its contents can only be neutralized by the action of effective irrigation with appropriate tissue dissolvent properties and antimicrobial activity solution or with the addition of use of intracanal medications.
Apical deltas are defined as an intricate system of spaces within the root canal that allows free passage of blood vessels and nerves from the periapical compartment to the pulp tissue [52, 53]. The apical delta is different from the accessory canal in which the main pulp canal is still distinguishable. The prevalence of apical deltas in human permanent teeth varies among populations, and the type and locations of tooth and methods of study. High prevalence of apical deltas is found in maxillary second premolars, mandibular lateral incisors, and mandibular second premolars [22]. Among American population, Vertucci [18] reported that the incidence of apical deltas was 5, 6, and 8% in the mandibular central incisors, lateral incisors, and canines, respectively. However, Çalişkan et al. [22] reported that the prevalence of apical deltas in those teeth was 9.8, 23.5 and 7.8% in a Turkish population. Apical deltas have been reported to be of great importance in endodontics because they are difficult to be instrumented during chemical-mechanical preparation. Furthermore, their long vertical extension may cause failure of the apical surgery if not involved during apical resection [54]. Gao et al. [55] reported that the median vertical distance of the apical delta was 1.87 mm with 13% of them more than 3 mm. Therefore, resection of the apical 3 mm of a root may include the whole apical delta and residual microorganisms from 87% of roots with apical delta.
A thin communication can occur between two or more canals in the same root or between vascular elements in tissues [56]. Green [23] described this corridor as a “ribbon shaped passage.” He found this corridor in 22% of mandibular incisors. An isthmus is formed when an individual root projection is unable to close itself off. Any root that contains two root canals has the potential to contain an isthmus [57]. It may contain tissue remnants and necrotic debris, which participate in microorganisms’ growth resulting in root canal treatment failure [58]. Therefore, knowledge of the root canal anatomy is essential for complete cleaning of the root canal and successful endodontic treatment [11]. Isthmus classification was described by Hsu and Kim et al. [59]. They classified isthmus into five types: Type I—two canals with no notable communication; Type II—a hair-thin connection between the two main canals; Type III—differs from Type II because of the presence of three canals instead of two; Type IV—an isthmus with extended canals into the connection; and Type V—there is a true connection or wide corridor of tissue between two main canals. Mauger reported that isthmus was present in 20% of the teeth at the 1-mm level, 30% at 2 mm, and 55% at 3 mm [27]. Estrela et al. [60] demonstrated high prevalence of both partial and complete isthmii in mandibular lateral incisors (47.6%) compared with mandibular central incisors (33.3%). On the other hand, Arslan et al. [38] found a low incidence (3.7%) of intracanal communication among Turkish population. A similar study done by Haghanifar [61] found the prevalence of complete isthmus in the mandibular anterior teeth ranged from 3 to 5%.
As a result of large width of the root canal buccolingually than mesiodistally, mandibular incisors have oval and flattened canals [25]. The overall prevalence of long oval root canals in the apical region in mandibular incisors is >50% [25]. When using rotary files, these oval-shaped canals are a challenge for proper shaping of the canal. This is because rotary instrumentation cannot touch all the canal walls, leaving behind untouched area. To improve mechanical apical debridement, the use of instruments up to an ISO size 100 is required to avoid leaving untouched area on the buccal and/or lingual walls of the canal [62]. However, using files with large taper or tip may cause lateral or apical perforation of the root as the root has a narrower diameter in the mesiodistal direction. Therefore, it stresses the use of good chemical disinfection protocol on these teeth. Canals are considered as oval, long oval, and flattened when the ratio between the maximum and the minimum cross-sectional diameter is <2:1, 2–4:1, and >4:1, respectively. Apical foramina are the main apical opening of the root canal. It is the main exit of the root canal onto the external root surface. Variation in the number and position of apical foramina is especially seen in mandibular incisors with two canals. The apical foramen coincides with the anatomical apex in 17–52.2% of the cases [19, 22, 33, 57, 63].
A number of studies (17.33%) reported that the position and the number of the apical foramen vary according to the race. Al-Qudah and Awawdeh [33] reported that more than half of the roots (52.2%) had centrally located foramina and 47.8% had laterally located foramina. Apical deltas were observed in only eight teeth (1.8%), and among mandibular incisors with two canals, single foramen was more prevalent than two apical foramina. Miyashita et al. [17] reported that only 3% of the mandibular incisors containing two canals had two foramina. He also found that 67.9% of mandibular incisors with curved root had eccentrically located foramina toward the labial direction and none of the canals were curved lingually.
According to Walker [63], the distance between the apical foramen and the most apical end of the root ranges between 0.2 and 2.0 mm. The diameter of the apical foramen of mandibular incisors has been reported to be as 262.5 μm.
Anomaly (Gk, anomalos; irregular) is a deviation from what is regarded as normal [64]. These abnormalities may occur, in terms of size or shape, to either crown or root. WHO listed the following dental anomalies: concrescence, fusion, gemination, dens evaginatus, dens in dente, dens invaginatus, enamel pearls, macrodontia, microdontia, peg-shaped teeth, taurodontism, and tuberculum paramolare [65]. Anomalies of permanent mandibular incisors regarding the crown and root shape are extremely rare. However, few case reports have registered anomalies associated with mandibular incisors. As an example, dens invaginatus, a deep surface invagination of the crown or root, which is lined by enamel and resulting from the invagination of the enamel organ into the dental papilla during odontogenesis, can be seen in these teeth [66]. Dens invaginatus has been classified into three categories according to the depth of invagination and communication with the periapical tissue or periodontal ligament [67].
The prevalence of this anomaly has been found to range from 0.25 to 5.1% of the population [66]. More commonly, dens invaginatus occurs in the maxillary permanent lateral incisors. Also, it may occur in maxillary central incisors, premolars, canines, and molars. It usually occurs unilaterally, but bilateral cases have also been reported [68]. Occurrence of dens invaginatus in mandibular teeth is very rare. When it occurs in mandibular incisors, the central incisor has a higher incidence compared with lateral incisor [69, 70].
Talon cusp is also a rare developmental anomaly defined as an additional cusp that projects predominantly from the labial or lingual surface of primary or permanent anterior teeth [71]. Mellor and Ripa [72] named this anomaly “talon cusp” as it resembles the shape of an eagle’s talon. Talon cusp was classified by Hattab [73] as follows:
Radiographically, the talon cusp may appear typically as a V-shaped radiopacity, starting from the cervical third of the crown. Most of the talon cusps occur in the maxillary lateral incisors (55%), followed by maxillary central incisors (32%) and maxillary canines (9%) [71]. Although it is rarely seen in mandibular teeth [74], Gündüz and Celenk [43] studied the site distribution of talon cusp among Turkish population and found only 3% of talon cusp was seen in the mandibular right central incisors.
Another rare developmental anomaly that has been reported to occur in mandibular central incisor is “Gemination” [75]. It is a rare anomaly that arises when the tooth bud of a single tooth attempts to divide. The structure most often presents as two crowns, either totally or partially separated, with a single root and one root canal [76]. In the anterior region, gemination can cause poor esthetic appearance due to irregular morphology. In addition, these teeth are more susceptible to periodontal disease and caries, if deep groove is present [77, 78].
Fusion is another developmental anomaly which can occur in these teeth. Contrary to gemination, fusion is defined as the union of two or more separately developing tooth germs during odontogenesis, when the crown is not yet mineralized at the dentinal level, yielding a single large tooth [79]. Depending on the stage of development at the time of union, the pulp might be merged or separated [80]. Fusion is more frequently seen in primary dentition, but it may occur in both dentitions. If it occurs in permanent dentition, the vast majority of permanent teeth fusion cases are seen in maxillary teeth. Although, the incidence of fusion of mandibular incisors is rare, mandibular central incisors have been reported to fuse with a supernumerary tooth [81] and bilaterally with the adjacent lateral incisor [82].
It should be emphasized that special attention is required during root canal treatment owing to the abnormal morphology of the crown and the complexity of the root canal system in fused teeth.
Mandibular incisors are prone to endodontic treatment as a result of several reasons. Due to their location in the jaw, they are prone to traumas that result in tooth fracture which may necessitate root canal therapy. Moreover, their proximity to the opening of the sublingual and submandibular ducts increases the incidence of dental caries as a result of lingual deposition of calculus. Therefore, an accurate knowledge of the external and internal anatomy of these teeth is an essential prerequisite to carry out root canal treatment. They often have two canals that are buccolingually located and the lingual canal usually is missed. Therefore, the dentist should extend the access preparation in lingual direction to locate the lingual canal which is usually below the cingulum. In case of two canals, Type II canal is the most prevalent configuration where the buccal canal is the most straight and easiest to be located. Consequently, it is recommended to instrument and fill these canals till the apex whereas the lingual canal merges with the labial canal. Presence of an isthmus may complicate the root canal disinfection as it may contain tissue remnants and necrotic debris, hence irrigation and activation are very essential to overcome these anatomical difficulties.
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His studies in robotics lead him not only to a PhD degree but also inspired him to co-found and build the International Journal of Advanced Robotic Systems - world's first Open Access journal in the field of robotics.",institutionString:null,institution:{name:"TU Wien",country:{name:"Austria"}}},{id:"441",title:"Ph.D.",name:"Jaekyu",middleName:null,surname:"Park",slug:"jaekyu-park",fullName:"Jaekyu Park",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/441/images/1881_n.jpg",biography:null,institutionString:null,institution:{name:"LG Corporation (South Korea)",country:{name:"Korea, South"}}},{id:"465",title:"Dr",name:"Christian",middleName:null,surname:"Martens",slug:"christian-martens",fullName:"Christian Martens",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"479",title:"Dr.",name:"Valentina",middleName:null,surname:"Colla",slug:"valentina-colla",fullName:"Valentina Colla",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/479/images/358_n.jpg",biography:null,institutionString:null,institution:{name:"Sant'Anna School of Advanced Studies",country:{name:"Italy"}}},{id:"494",title:"PhD",name:"Loris",middleName:null,surname:"Nanni",slug:"loris-nanni",fullName:"Loris Nanni",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/494/images/system/494.jpg",biography:"Loris Nanni received his Master Degree cum laude on June-2002 from the University of Bologna, and the April 26th 2006 he received his Ph.D. in Computer Engineering at DEIS, University of Bologna. On September, 29th 2006 he has won a post PhD fellowship from the university of Bologna (from October 2006 to October 2008), at the competitive examination he was ranked first in the industrial engineering area. He extensively served as referee for several international journals. He is author/coauthor of more than 100 research papers. He has been involved in some projects supported by MURST and European Community. His research interests include pattern recognition, bioinformatics, and biometric systems (fingerprint classification and recognition, signature verification, face recognition).",institutionString:null,institution:null},{id:"496",title:"Dr.",name:"Carlos",middleName:null,surname:"Leon",slug:"carlos-leon",fullName:"Carlos Leon",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Seville",country:{name:"Spain"}}},{id:"512",title:"Dr.",name:"Dayang",middleName:null,surname:"Jawawi",slug:"dayang-jawawi",fullName:"Dayang Jawawi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Technology Malaysia",country:{name:"Malaysia"}}},{id:"528",title:"Dr.",name:"Kresimir",middleName:null,surname:"Delac",slug:"kresimir-delac",fullName:"Kresimir Delac",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/528/images/system/528.jpg",biography:"K. 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From Old Problems to New Challenges"},signatures:"Andreas Schmeling, Pedro Manuel Garamendi, Jose Luis Prieto and María Irene Landa",authors:[{id:"34264",title:"Prof.",name:"Pedro Manuel",middleName:null,surname:"Garamendi Gonzalez",slug:"pedro-manuel-garamendi-gonzalez",fullName:"Pedro Manuel Garamendi Gonzalez"}]},{id:"19161",doi:"10.5772/19234",title:"Diagnostic of Drowning in Forensic Medicine",slug:"diagnostic-of-drowning-in-forensic-medicine",totalDownloads:8196,totalCrossrefCites:9,totalDimensionsCites:18,abstract:null,book:{id:"243",slug:"forensic-medicine-from-old-problems-to-new-challenges",title:"Forensic Medicine",fullTitle:"Forensic Medicine - From Old Problems to New Challenges"},signatures:"Audrey Farrugia and Bertrand Ludes",authors:[{id:"34146",title:"Dr.",name:"Audrey",middleName:null,surname:"Farrugia",slug:"audrey-farrugia",fullName:"Audrey Farrugia"},{id:"49284",title:"Dr.",name:"Bertrand",middleName:null,surname:"Ludes",slug:"bertrand-ludes",fullName:"Bertrand Ludes"}]},{id:"19172",doi:"10.5772/22792",title:"Advanced Medical Imaging and Reverse Engineering Technologies in Craniometric Study",slug:"advanced-medical-imaging-and-reverse-engineering-technologies-in-craniometric-study",totalDownloads:4535,totalCrossrefCites:2,totalDimensionsCites:6,abstract:null,book:{id:"243",slug:"forensic-medicine-from-old-problems-to-new-challenges",title:"Forensic Medicine",fullTitle:"Forensic Medicine - 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From Old Problems to New Challenges"},signatures:"Ljiljana Vasović, Milena Trandafilović, Ivan Jovanović, Slađana Ugrenović, Slobodan Vlajković and Jovan Stojanović",authors:[{id:"34455",title:"Prof.",name:"Ljiljana",middleName:null,surname:"Vasovic",slug:"ljiljana-vasovic",fullName:"Ljiljana Vasovic"},{id:"47169",title:"Dr.",name:"Milena",middleName:null,surname:"Trandafilovic",slug:"milena-trandafilovic",fullName:"Milena Trandafilovic"},{id:"47170",title:"Dr.",name:"Ivan",middleName:null,surname:"Jovanovic",slug:"ivan-jovanovic",fullName:"Ivan Jovanovic"},{id:"47171",title:"Dr.",name:"Sladjana",middleName:null,surname:"Ugrenovic",slug:"sladjana-ugrenovic",fullName:"Sladjana Ugrenovic"},{id:"47172",title:"Dr.",name:"Slobodan",middleName:null,surname:"Vlajkovic",slug:"slobodan-vlajkovic",fullName:"Slobodan Vlajkovic"},{id:"47179",title:"Prof.",name:"Jovan",middleName:null,surname:"Stojanovic",slug:"jovan-stojanovic",fullName:"Jovan Stojanovic"}]},{id:"19160",doi:"10.5772/18161",title:"Death Scene Investigation from the Viewpoint of Forensic Medicine Expert",slug:"death-scene-investigation-from-the-viewpoint-of-forensic-medicine-expert",totalDownloads:27389,totalCrossrefCites:2,totalDimensionsCites:6,abstract:null,book:{id:"243",slug:"forensic-medicine-from-old-problems-to-new-challenges",title:"Forensic Medicine",fullTitle:"Forensic Medicine - From Old Problems to New Challenges"},signatures:"Serafettin Demirci and Kamil Hakan Dogan",authors:[{id:"30612",title:"Prof.",name:"Kamil Hakan",middleName:null,surname:"Dogan",slug:"kamil-hakan-dogan",fullName:"Kamil Hakan Dogan"},{id:"32211",title:"Dr.",name:"Serafettin",middleName:null,surname:"Demirci",slug:"serafettin-demirci",fullName:"Serafettin Demirci"}]}],mostDownloadedChaptersLast30Days:[{id:"19160",title:"Death Scene Investigation from the Viewpoint of Forensic Medicine Expert",slug:"death-scene-investigation-from-the-viewpoint-of-forensic-medicine-expert",totalDownloads:27389,totalCrossrefCites:2,totalDimensionsCites:6,abstract:null,book:{id:"243",slug:"forensic-medicine-from-old-problems-to-new-challenges",title:"Forensic Medicine",fullTitle:"Forensic Medicine - From Old Problems to New Challenges"},signatures:"Serafettin Demirci and Kamil Hakan Dogan",authors:[{id:"30612",title:"Prof.",name:"Kamil Hakan",middleName:null,surname:"Dogan",slug:"kamil-hakan-dogan",fullName:"Kamil Hakan Dogan"},{id:"32211",title:"Dr.",name:"Serafettin",middleName:null,surname:"Demirci",slug:"serafettin-demirci",fullName:"Serafettin Demirci"}]},{id:"57199",title:"Negative Autopsy in Infant and Juvenile Population: Role of Cardiac Arrhythmias",slug:"negative-autopsy-in-infant-and-juvenile-population-role-of-cardiac-arrhythmias",totalDownloads:1405,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"Negative autopsy is a post-mortem examination in which a comprehensive analysis does not provide a cause of death. These include situation of death, anatomical and histological analysis, toxicology and microbiological study. A low part of autopsies remain without a conclusive cause of death, but all these cases are usually seen in young population, apparently healthy who died suddenly and unexpectedly. In these situations a cardiac arrhythmia is suspected as cause of death and genetic testing is recommended despite not regularly performed. Sudden death is a natural and unexpected decease that occurs in apparently healthy people, or whose disease was not severe enough to expect a fatal outcome. It can be due to several pathologies, usually of cardiac cause and called sudden cardiac death. In infants and young people, both long QT syndrome and catecholaminergic polymorphic ventricular tachycardia are main causes in negative autopsies. These genetic diseases lead to ventricular fibrillation, syncope and sudden cardiac death in a normal heart. Unfortunately, sudden cardiac death could be the first manifestation of the diseases, being early identification and prevention a crucial point in current medical practice. This chapter focuses on sudden death and negative autopsy in young population, mainly due to cardiac arrhythmias.",book:{id:"6262",slug:"post-mortem-examination-and-autopsy-current-issues-from-death-to-laboratory-analysis",title:"Post Mortem Examination and Autopsy",fullTitle:"Post Mortem Examination and Autopsy - Current Issues From Death to Laboratory Analysis"},signatures:"Georgia Sarquella-Brugada, Sergi Cesar, Anna Fernandez-Falgueras,\nMaria Dolores Zambrano, Anna Iglesias, Josep Brugada, Ramon\nBrugada and Oscar Campuzano",authors:[{id:"54165",title:"Prof.",name:"Ramon",middleName:null,surname:"Brugada",slug:"ramon-brugada",fullName:"Ramon Brugada"},{id:"54168",title:"Dr.",name:"Oscar",middleName:null,surname:"Campuzano",slug:"oscar-campuzano",fullName:"Oscar Campuzano"},{id:"218478",title:"Dr.",name:"Georgia",middleName:null,surname:"Sarquella-Brugada",slug:"georgia-sarquella-brugada",fullName:"Georgia Sarquella-Brugada"},{id:"218479",title:"Dr.",name:"Sergi",middleName:null,surname:"Cesar",slug:"sergi-cesar",fullName:"Sergi Cesar"},{id:"218480",title:"MSc.",name:"Anna",middleName:null,surname:"Fernandez-Falgueras",slug:"anna-fernandez-falgueras",fullName:"Anna Fernandez-Falgueras"},{id:"218482",title:"Dr.",name:"Maria Dolores",middleName:null,surname:"Zambrano",slug:"maria-dolores-zambrano",fullName:"Maria Dolores Zambrano"},{id:"218483",title:"MSc.",name:"Anna",middleName:null,surname:"Iglesias",slug:"anna-iglesias",fullName:"Anna Iglesias"},{id:"218484",title:"Prof.",name:"Josep",middleName:null,surname:"Brugada",slug:"josep-brugada",fullName:"Josep Brugada"}]},{id:"57778",title:"Defining Dental Age for Chronological Age Determination",slug:"defining-dental-age-for-chronological-age-determination",totalDownloads:2574,totalCrossrefCites:1,totalDimensionsCites:3,abstract:"Dental age assessment is one of the most reliable methods of chronological age estimation used for criminal, forensic and anthropologic purposes. Visual, radiographic, chemical and histological techniques can be used for dental age estimation. Visual method is based on the sequence of eruption of the teeth and morphological changes that are caused due to function such as attrition, changes in color that are indicators of aging. Radiographs of the dentition can be used to determine the stage of dental development of the teeth from initial mineralization of a tooth, crown formation to root apex maturation. Histological methods require the preparation of the tissues for detailed microscopic examination. The chemical analysis of dental hard tissues determines alterations in ion levels with age, whereas the histological and chemical methods are invasive methods requiring extraction/sectioning of the tooth. In this chapter, the different techniques and considered studies were overviewed in conjunction with their advantages and disadvantages. 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