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In this chapter, we discuss the causes of hyperglycemia, including drug-induced hyperglycemia, highlighting the importance and approaches to prevention and management of hyperglycemia. We focus on the role and rationale for the use of metformin for the prevention of hyperglycemia, presenting the evidence that supports its use for this indication.
Hyperglycemia, which literally means ‘high blood glucose’ levels, refers to the elevation of blood glucose concentrations above the normal range. Specifically, it refers to fasting blood glucose levels greater than 7.0 mmol/L (126 mg/dl) or 2-hour postprandial blood glucose levels greater than 11.0 mmol/L (200 mg/dl) [1].
Mild, transient hyperglycemia is largely asymptomatic. However, prolonged uncontrolled hyperglycemia is associated with various symptoms including the classic hyperglycemic triad of polyuria, polydipsia, and polyphagia, as well as blurred vision, dehydration, weight changes (gain or loss), generalized fatigue, abdominal discomfort, nausea, vomiting and muscle cramps [1, 2]. Complications arise when the hyperglycemia is severe and/or persists over an extended period. Frequent infections, erectile dysfunction and poor wound healing are associated with prolonged hyperglycemia. Chronic hyperglycemia can also lead to many serious life-threatening complications involving damage to the kidneys (nephropathy), retina (retinopathy), nervous system (peripheral neuropathy) and cardiovascular system (myocardial infarction, stroke) [1, 2, 3, 4, 5].
Blood glucose levels reflect the dynamic balance between, on the one hand, dietary glucose absorption and hepatic glucose production and, on the other hand, glucose uptake and utilization by peripheral tissues. Except for dietary glucose absorption, these complex and interrelated processes are under the control of the hormone insulin and, to a lesser extent, other counter-regulatory hormones such as glucagon, catecholamines, cortisol and growth hormone [1, 6]. Hyperglycemia arises from an imbalance in these processes that determine blood glucose levels.
The greatest quantitative determinant for hyperglycemia is dysfunction in pancreatic islet cell activity which affects insulin release from the pancreas in response to. The pathophysiology of hyperglycemia also entails a resulting degree of insulin resistance and impairment in homeostatic glucose regulation. Insulin resistance results in decreased uptake of glucose by insulin-sensitive tissues as well as a consequential increase in endogenous glucose production. This all leads to hyperglycemia [7]. The elevation of blood glucose levels during the fasting state is directly proportional to the increase in hepatic glucose production while that of the postprandial state is connected to insufficient suppression of glucose output plus a defect in the stimulation of insulin hormone on recipient tissues like skeletal muscle [8].
The progression of this imbalance in blood glucose homeostasis over time leads to the development of diabetes, a chronic disease affecting glucose metabolism that occurs due to either insufficient production of insulin by the pancreas, or inadequate response by tissues to insulin [9]. The development of diabetes can be delayed or prevented by targeting the early prevention and/or reversal of hyperglycemia, as well as by inhibiting the development of hyperinsulinemia-induced insulin resistance [10]. This would also delay progression of prediabetic states to diabetes [11].
In addition to diabetes, there are a myriad of other causes of hyperglycemia, i.e., non-diabetic hyperglycemia. Disorders that compromise pancreatic function (pancreatic cancer, cystic fibrosis, chronic pancreatitis, etc.) or affect the glucose counter-regulatory hormones (pheochromocytoma, acromegaly, Cushing syndrome) cause hyperglycemia. Transient hyperglycemia may arise consequent to abnormally high carbohydrates in the diet, dextrose infusion and total parental nutrition. Acute or serious illness or injury may also bring about transient hyperglycemia referred to as stress hyperglycemia or hospital-related hyperglycemia [1, 12].
Drug-induced hyperglycemia refers to the clinically relevant elevation of blood glucose levels caused by drugs [13]. Whereas drug-induced hyperglycemia is often mild and asymptomatic, severe hyperglycemia may occur particularly in predisposed patients, such as those with pre-existing pancreatic dysfunction or insulin resistance. Drug-induced hyperglycemia can occur in adults and children alike, and certain patient factors are known to increase the risk of drug-induced hyperglycemia, such as obesity, sedentary lifestyle, stress, illness, history of gestational diabetes, or a family history of diabetes [6, 14].
Many classes of drugs have been implicated in causing hyperglycemia via various mechanisms. Some drugs cause hyperglycemia by reducing insulin production/secretion (glucocorticoids, β-receptor antagonists, thiazide diuretics, calcium-channel blockers, phenytoin, pentamidine, calcineurin inhibitors, protease inhibitors), including by direct damage to pancreatic cells (glucocorticoids, pentamidine, statins). Glucocorticoids, β-receptor antagonists and thiazide diuretics also promote hepatic glucose production and reduce insulin sensitivity. Other classes of drugs that reduce peripheral tissue sensitivity to insulin include atypical antipsychotics, antidepressants, oral contraceptives, statins, nucleoside reverse transcriptase inhibitors and protease inhibitors [1, 6, 14, 15, 16]. Hyperglycemia is one of the common adverse effects of the anticancer agent L-asparaginase, which inhibits insulin synthesis by depleting available asparagine in pancreatic cells in addition to impairing insulin receptor activity and promoting peripheral tissue resistance to insulin [14]. Monoclonal antibodies such as nivolumab and pembrolizumab may cause severe hyperglycemia by triggering the autoimmune-mediated destruction of pancreatic cells [17, 18]. β2-receptor agonists cause hyperglycemia by promoting hepatic and muscle glucose production [19]. The various mechanisms of drug-induced hyperglycemia and the classes of drugs implicated are shown in Figure 1.
Mechanisms of drug-induced hyperglycemia and implicated classes of drugs.
The overall occurrence of drug-induced hyperglycemia is not known and would obviously vary between individual drugs. There is a lack of data on the burden of drug-induced hyperglycemia for specific drugs, and a few studies have attempted to address this gap. For example, the incidence of corticosteroid-related hyperglycemia in patients treated with high dose corticosteroids has been estimated to be in excess 50% [20, 21]. Comparably high prevalence has been reported for clozapine [22]. These and other similar findings strongly suggest that the risk of drug-induced hyperglycemia (alongside the risk of new-onset diabetes) is real.
The onset of drug-induced hyperglycemia varies on the medication administered. At the time of or shortly after initiating corticosteroids, blood glucose levels may be altered, whereas patients on hydrochlorothiazide may not experience altered levels for weeks or longer, depending on the dose given. In regard to second generation antipsychotics (SGAs), a consensus statement developed by the American Diabetes Association (ADA) in conjunction with other medical organizations recommends monitoring fasting blood glucose for 12 weeks after initiation of therapy and annually thereafter in those without diabetes. However, cases involving hyperglycemic crises have been reported within weeks of starting SGAs [23].
The common medical occurrence of hyperglycemic states has yet to be given the due attention it deserves, considering the numerous consequences it bears to patients and the healthcare fraternity. The existing reality of numerous patients suffering from hyperglycemia of varied cause provides an overwhelming patient load, unmatched by the number of specialized providers. However, the management of hyperglycemia has continually posed a great challenge mainly from a lack of standardized protocols [24]. Currently, lack of knowledge and consensus on strategies of management play a significant role in its mismanagement.
Insulin resistance and the resulting compensatory hyperinsulinemia is considered to preclude the development of type 2 diabetes. Hyperglycemia prophylaxis is thus highly attractive based on the numerous socio-economic benefits it confers to patients and the healthcare system. Several studies have demonstrated the advantages gained from preventing elevations of blood glucose levels across a divergent patient portfolio. Research has broadly focused on management of hyperglycemia regardless of the cause, which underlies the common pathways involved in the development of hyperglycemia.
The primary strategy employed in hyperglycemia management is insulin [25]. Consensus arrived at by ADA and European Association for the Study of Diabetes (EASD) outline the management of hyperglycemia in type 2 diabetes patients. These guidelines have also been adopted in the prevention of hyperglycemia from other causes, including drug-induced hyperglycemia. The guidelines recommend the use of insulin in all hospitalized patients, with discontinuation of oral hypoglycemic medication [26, 27]. Stoppage of the drugs is on the basis that majority of hospitalized patients present with concurrent conditions and/or physiological dysfunctions that tend to contraindicate continued use of these medications if already prescribed. The pharmacokinetics of oral medication, which tend to have a slow onset of action, disallows for rapid dose adjustment to changing patient needs [28]. Therefore, it is recommended that critically ill patients be treated with a continuous insulin infusion while non-critically ill patients are initiated on subcutaneous (SC) insulin. An individualized dose adjustment for insulin is advised across major studies [26, 29]. Resumption of oral diabetic agents (ODA) when transitioning from inpatient to outpatient setting, with careful consideration given to previous insulin dosing, is advised upon successful treatment. A study involving patients without diabetes recommended the administration of intravenous (IV) insulin infusion in patients with serum blood glucose level values of greater than 10 mmol/L, with a target of achieving serum blood glucose levels of 7.8–10 mmol/L in non-critical settings and less than 7.8 mmol/L in an outpatient setting [30].
Despite numerous recommendations, challenges faced by providers during insulin administration cannot be overlooked. The biggest impediment to insulin use in management of drug-induced hyperglycemia in the affected population is the unavoidable side effect of hypoglycemia [31]. Unfortunately, insulin treatment is the most common risk factor for inpatient hypoglycemia. The incidence of hypoglycemia is approximately 30% in elderly patients, in spite of using low dose insulin and oral diabetic agents [28]. This is associated with increased mortality rate and prolonged hospital stays. Hence, constant monitoring of blood glucose levels is necessary.
Dose adjustments using patients’ weight is perceived to be safe and effective as long as close monitoring is done. However, this is not always feasible, let alone practical with many patients. So too is the recommendation of individualizing glycemic targets for patients based on clinical status, risk of hypoglycemia and patient comorbidities, no matter the benefit it confers. This is because the number of patients with drug-induced hyperglycemia cannot be matched to the number of specialized health care workers required to meet this need.
Herein lies the difficulty as many patients are unable to achieve the close monitoring desired, let alone manage the expected side effects in a home-based set up. Even in hospitalized patients, lack of protocols for dose adjustment poses a hindrance in adequate control of elevated blood glucose levels. Hypoglycemia presents a consequential effect that should be carefully considered in hyperglycemia management. Any chosen medication, in addition to lifestyle interventions, should ideally be one that is safe, effective, economical and with minimal side effects.
Non-insulin medications provide a practical alternative to achieving glycemic control. These agents may also confer a non-glycemic benefit whilst regulating the fluctuations in blood glucose levels. Alternatives among non-insulin medication include metformin, sulphonylureas, glinides, thiazolidinediones, glucagon-like peptide-1 (GLP-1) receptor agonists, and sodium–glucose cotransporter2 (SGLT2) inhibitors.
However, the side effects of each of these agents must also be considered. For example, SGLT2 inhibitors reduce blood glucose levels by preventing proximal tubular reabsorption in the kidney. This has been shown to effectively reduce glycated hemoglobin A1c (HbA1c) levels by 0.6–1.0%. They are also associated with a low risk of hypoglycemia. However, the dehydration side effects make these agents contraindicated in renal dysfunction. They also bear an increased risk of urinary and genital tract infections and are related with the development of diabetic ketoacidosis among diabetic patients [32]. Such a profile tends to limit the use of these agents. Metformin use is contraindicated in the presence of any possible indication for iodinated contrast media and in renal insufficiency while thiazolidinediones are associated with fluid retention. On the other hand, sulfonylureas and glinides result in hypoglycemia in most patients while GLP-1 receptor antagonists can cause nausea and hence need to be withheld in critical patients. In spite of the many side effects of oral diabetic agents and the recommendation of using insulin as first line, recent studies have leaned towards the adoption of the oral diabetic agents. The drug most endorsed based on clinical evidence has been metformin [33].
The pathophysiology of hyperglycemia entails a degree of insulin resistance and results in decreased uptake of glucose by insulin-sensitive tissues as well as a consequential increase in endogenous glucose production [7]. Dysfunction in the activity of pancreatic islet cells affects insulin release in response to rising blood glucose levels. Targeting the prevention and/or reversal of dysglycemia and insulin resistance is the principal behind preventing the development of hyperglycemia [11]. Any agent used in prevention of hyperglycemia must therefore target these pathways, thereby partially or completely eliminating its development.
Metformin can rightfully be considered for hyperglycemia prevention and treatment in cases of insulin resistance. Metformin is a first-line agent in treatment of type 2 diabetes mellitus. Recent studies have shown it confers a greater benefit to patients than the other oral diabetic agents, which has led to its recommendation for use in the prevention of hyperglycemia and prediabetes in at risk patients [34, 35, 36].
Metformin prevents hyperglycemia by hastening the clearance of glucose [37, 38]. It causes a reduction in hyperglycemia and hyperinsulinemia [39]. This facilitates a consequent decline in high insulin and high blood glucose levels, with no effect on insulin secretion. The primary mechanism involved in lowering blood glucose levels is through improving hepatic and peripheral tissue sensitivity to insulin [40]. It inhibits the production of glucose by the liver whilst enhancing uptake of circulating glucose and its utilization in peripheral tissues such as muscle and adipose tissue.
Hepatic gluconeogenesis is an energy-demanding process in which synthesis of one molecule of glucose from lactate or pyruvate requires four molecules of ATP and two molecules of GTP. Metformin suppresses hepatic gluconeogenesis by causing a reduction of cellular ATP levels [41]. Molecularly, metformin appears to inhibit mitochondrial respiration. The resulting shift in cellular energy balance increases the activity of AMP-activated protein kinase (AMPK), which promotes the action of insulin and reduces hepatic gluconeogenesis [42]. AMPK acts as a cell energy sensor: it plays a role in energy balance at the cellular and body level by adapting to changes in the concentration of AMP/ADP relative to ATP [43]. Upon activation by a decrease in cellular energy levels, AMPK initiates a change from anabolic to catabolic pathways that consume ATP. This stimulates the uptake and use of glucose and oxidation of fatty acids, in addition to the suppression of hepatic glucose production. Metformin’s’ inhibition of the mitochondrial complex is the basis of its effect as observed through the change in the ratios of AMP/ATP or ADP/ATP after its administration [44]. Multiple studies have demostrated that one of the mechanisms of action of metformin is the disruption of mitochondrial complex I [45, 46].
Metformin may also modulate the gut-brain-liver axis through the activation of a duodenal AMPK-dependent pathway, as has been demonstrated in rats. This effect involves activation of protein kinase A (Pka) by GLP-1 in duodenal enterocytes, and results in suppression of hepatic glucose production [47]. It has been shown that glucocorticoid therapy leads to changes in the activation of AMPK in Cushing’s syndrome patients and in vitro in human adipocytes, effects that were reversed with metformin in human adipocytes. These indicate the likelihood of converse effects of steroids and metformin in the AMPK signaling pathway, as well as the overriding of steroid effects by metformin [44, 48]. Supporting studies demonstrate that steroid-related increase in glucose levels can be prevented with an AMPK activator [49].
Another postulated mechanism of action for metformin is by causing an increase in circulating cyclic adenosine monophosphate (cAMP) which in turn opposes the hyperglycemic action of glucagon [42, 50]. Metformin has also been postulated to increase the concentration of Glucagon-like peptide-1 (GLP-1) by enhancing site production as well as subsequently decreasing its degradation in circulation and specific tissues via inactivation of the enzyme dipeptide peptidase-4 (DPP-4). Additionally, metformin may induce up regulation of GLP-1receptors on beta cell surfaces of the pancreas. This can aid in ameliorating the beta cell dysfunction associated with hyperglycemia via the enhancement of the role of GLP-1 on glucose dependent release of insulin [11].
Metformin can rightfully be considered for hyperglycemia prevention and treatment in cases of insulin resistance. Metformin has been identified as a first line agent in treatment of type 2 diabetes mellitus. Recent studies have shown that it confers a greater benefit to patients than the other oral diabetic agents, which has led to its recommendation for use in the prevention of prediabetes in at risk patients [34, 35, 51]. Presently though, only a few nations have formally adopted this proposal such as Poland, Philippines and Turkey but many may adopt it in the near future based on the emerging evidence [11]. Metformin overrides most of the factors that contribute to poor glycemic management like inaccessibility to medicine and fear of developing hypoglycemia. This improves patient perception on its use regardless of the minimal side effects. In addition, it has been demonstrated to confer long term benefit to those who use it prophylactically. A study that followed up patients from a diabetes prevention program after 15 years found that the metformin treatment arm had a 17% lower incidence for developing type 2 diabetes than the placebo arm. This was determined using the HbA1c parameter, in which 36% of the patients had a risk reduction for diabetes development [34].
In a prospective observational study in persons with normal glucose tolerance and hyperinsulinemia, a dose of 2.55 ± 0.2 g/day of metformin restored physiological insulin secretion by decreasing fasting and post-glucose load hyperinsulinemia in the oral glucose tolerance test (OGTT). Over the observation period, the effect of metformin on the reduction of hyperinsulinemia increased over time, peaking after 1 year of treatment. The ability to lower fasting blood glucose levels also improved with time. Fasting blood glucose levels reached normoglycemic range at 3 months and remained so until the end of the 1 year observation period, with no development of hypoglycemia [39]. A substantial decrease in hyperinsulinemia from high blood glucose levels has also been reported in metformin-treated patients based on an increase in the uptake of glucose [52]. The enhancement of insulin action reduces the load on the beta cells in insulin secretion thus can aid in ameliorating the beta cell dysfunction to an extent; this confers an advantage to patients predisposed to developing hyperglycemia.
In addition, a randomized controlled study showed that there was no significant difference in blood glucose levels between critically ill patients receiving 1000 mg of metformin daily versus a similar spectrum of patients receiving 50 International Units (IU) of regular insulin. Furthermore, metformin-treated patients had blood glucose levels subside to near-normal range [40]. The targeted desired blood glucose levels were achieved with metformin after three days while insulin failed to do the same.
In acute lymphoblastic leukemia patients with drug-induce hyperglycemia, metformin monotherapy controlled blood glucose in 12 out of 17 patients, without the need for insulin using a median dose of 1000 mg/day for a median of 6 days. Blood glucose levels never exceeded 11.1 mmol/L in 8 of the 12 patients. The one patient who developed hyperglycemia during relapse re-induction for leukemia treatment was effectively controlled using metformin alone [53]. Three of the patients given insulin therapy due to high blood glucose levels were eventually weaned off insulin to metformin alone. Additionally, in a controlled trial consisting of non-diabetic patients on glucocorticoids, metformin prevented an increase of 2-hour glucose AUC with, signifying glucose tolerance preservation. No changes in baseline and after 4 weeks metformin treatment was seen with the 2-hour glucose AUC whereas this parameter increased in the placebo group [54].
Similarly, the effect of metformin on prednisone-induced hyperglycemia (PIH) was observed on fasting and 2-hour post prandial glucose levels in hematological cancer patients. The fasting blood glucose readings indicated a proportion of prednisone-induced hyperglycemia of 72.7% and 14.3% in the control and treatment groups respectively. The proportion was slightly lower while using the 2-hour post prandial glucose, in which 54.5% of participants in the control group developed prednisone-induced hyperglycemia while none developed prednisone-induced hyperglycemia in the treatment group. Patients in the control group had 16 (95% CI 1.3–194.6) times the odds of developing prednisone-induced hyperglycemia compared to patients in the treatment group. Double daily dosing (1700 mg twice daily) was more effective in preventing prednisone-induced hyperglycemia [21]. This is supported by other studies that show that that a daily dose of metformin 1500 mg contributes to 80–85% glucose lowering effects [55].
The limitations attached to the full exploitation of metformin use include its relative contraindications in many hospitalized patients who present with comorbidities like renal insufficiency or unstable hemodynamic status. Metformin is contraindicated if serum creatinine is ≥133 mmol/L in men or ≥ 124 mmol/L in women. Emerging evidence shows that the established cut-off points for renal safety may be overly restrictive [56]. It has been argued that there is a need to relax these cut-offs and policies to allow use of this drug to patients with stable chronic kidney disease characterized by mild–moderate renal insufficiency [57, 58, 59].
The associated risk of lactic acidosis tends to deter the use of metformin in majority of the comorbid patients on drugs that predispose to the development of hyperglycemia. However, the studies that made such recommendations used a small percentage of the patient population, thus limiting the extrapolation of these recommendations to the greater public [60]. Fortunately, the incidence of metformin-induced lactic acidosis is rare and can be significantly reduced in at-risk patients by observing the necessary precautions [27, 56]. Other factors may also play a greater role in in being predictors of acidosis, such as dehydration, severe heart and renal failure. Thus, its benefits for use outweigh the potential risk of lactic acidosis.
Supporting evidence on avoidance of metformin use in certain cases is poor and inconsistent such as in patients undergoing radio-contrast imaging which theoretically predisposes patients to media-induced nephropathy, increasing the risk of lactic acidosis [56].
The benefits of metformin in the prevention of hyperglycemia are unmatched despite its list of contraindications. This has facilitated its expanded use based on its well-founded glycemic effects as well as numerous benefits conferred such as the beneficial effect on reduction of development of cardiovascular risk factors [61]. It confers good glycemic management that yields a substantial and enduring decrease in the onset and progression of micro vascular complications [60].
Moreover, large based clinical trials and systematic reviews have shown its beneficial effect of enhancing weight loss, even the weight loss associated with medicaments like antipsychotic agents [62, 63].
In summary, the suppression of glucose production by metformin’s direct effect plus the enhancement of hepatic insulin signaling will curb the development of drug-induced hyperglycemia. Metformin has been shown to reduce the incidence of hyperglycemia-related complications such as diabetes and risk factors for cardiovascular disease in patients with impaired glucose tolerance and fasting blood sugar [11, 64, 65]. This has led to its endorsement of use in patients with high risk of developing the aforementioned conditions [36].
Age-related macular degeneration (AMD) is a prevalent, progressive eye disease that is characterized by a late-onset neuro-degeneration of the photoreceptors (light-sensitive retinal cells) and their supporting tissues [1].
It is considered a highly disabling disease, as the macula (part of the eye responsible for sharp, clear vision) is the most damaged area of the retina, causing a gradual loss of central vision with subsequent difficulties in many activities of daily living (ADLs) for those affected, such as reading, driving, mobility or face recognition.
Globally, AMD is responsible for approximately 7% of blindness and 3% of visual impairment, making it the third most common cause of vision loss worldwide, and the first in industrialized countries [2, 3].
In economic terms, the total cost due to AMD is estimated to be approximately $343 billion, including $255 billion in direct healthcare costs (due to scheduled medical visits, treatment, rehabilitation, vision-related equipment, etc.) and $88 billion in indirect costs (due to injury, depression, loss of productivity, and social dependence as a consequence of blindness caused by the disease) [4]. Furthermore, the progressive growth and ageing of the population suggests that the magnitude of this issue will increase in the coming years, with the global prevalence of AMD expected to rise from 199 million people in 2020 to 288 million in 2040 [5].
From a clinical perspective, AMD can be classified into early and late stages. Patients with early AMD are usually asymptomatic and present yellowish drusen and pigmentary alterations in the macular area on fundus examination (Figure 1), while late stages of the disease, responsible for most visual loss attributed to AMD, are defined by the presence of signs indicating choroidal neovascularization (CNV) or geographic atrophy (GA) [6].
Large drusen appearing as yellowish subretinal spots present in a patient with early AMD from the Blue Mountains Eye Study [
In CNV (wet) AMD, abnormal blood vessels grow and break through to the neural retina (Figure 2). These new blood vessels are fragile and tend to leak blood, fluid and lipids, which can accumulate under the macular area, elevating it and distorting vision and eventually leading to the formation of fibrous scarring.
Recent-onset neovascular AMD on colour photography (left), spectral-domain optical coherence tomography (middle), and optical coherence tomography angiography showing appearance of choroidal new vessels (right) [
On the other hand, in atrophic (late dry) AMD, a gradually deterioration of the retinal pigmentary epithelium (RPE), choriocapillaris, and photoreceptors occurs (Figure 3). As both AMD forms progresses, detail in front of central visual field is lost and over time a blind spot (scotoma) may appear in the central visual field of the patient [8].
Large soft drusen surrounding an area of GA on colour fundus photography (left), fundus autofluorescence imaging (middle), and fluorescein angiography (right) [
Although the initial cause of AMD remains unclear, several risk factors have been linked to the development of the disease, such as age (>60 years), lifestyle (smoking, diet), cardiovascular disease and genetic markers [9].
This suggest that the pathogenesis of AMD is the result of a complex multifactorial interaction between environmental, functional, genetic and metabolic factors involving multiple biological pathways, including inflammation, angiogenesis, remodeling of the extracellular matrix, lipid metabolism and transport regulation, etc. [10, 11, 12].
In recent years, several epidemiological studies have reported a decrease in blindness and visual impairment associated with AMD [13, 14], which is likely to be attributed to improved diagnostic procedures, earlier diagnosis, slowing disease progression through micronutrient supplementation [15, 16], and the introduction of new therapies based on suppression of vascular endothelial growth factor (VEGF) [17].
Unfortunately, despite all this progress in AMD management, there is currently no effective treatment to cure the disease or reverse its course. However, in most patients, peripheral vision is preserved, allowing them to retain a certain level of autonomy.
On this basis, visual rehabilitation (VR) aims to provide these people with a range of strategies and behaviors to achieve the full potential of their remaining vision, improving their self-confident and independence and enabling them to return to a visually active life as much as possible. This philosophy aims at increasing awareness in low-vision patients, so they do not just focus on their loss or their impairment.
People who do not have AMD (e.g., family members, caregivers, and even some healthcare providers) often underestimate the effect of this condition, particularly in terms of visual function and quality of life (QoL) [18].
According to the World Health Organization’ (WHO), disability must include both the impairment of bodily structures or functions and the difficulty or limitation in performing a task and in participating in life situations [19].
This approach implies that the rehabilitation process cannot only focus on the aspects that directly affect the person, but must also deal with the society in which they live and the context that makes it possible for them to develop, in order to have a successful life.
Paying attention to this, comprehensive AMD care should give attention not only to the structural and functional condition of the eye, but also to the patient’s functioning in his or her specific surrounding. In this sense, the main difference between VR and other ophthalmic sub-specialties is that most of these sub-specialties are anatomically defined, while VR is functionally defined (Figure 4) [20].
Comprehensive AMD care diagram showing the areas of influence and differences between medical and rehabilitative care. Adapted from: [
To adequately cover all these aspects, the participation and collaboration of different professionals is necessary, since different goals often require different interventions [21]. This can be observed in the US and Europe models, where a wide range of professionals, varying from continent to continent, work together to achieve a successful rehabilitation.
Multidisciplinary low-vision teams usually require an ophthalmology, an optometrist, an occupational therapist and a rehabilitation teacher among other professionals specially trained in the evaluation of the patient’s remaining vision and the prescription of different low-vision aids (LVAs) [22]. However, prescription of these aids is only the first step in learning how to use them effectively, as training and continuous practice are essential to help the patient feel comfortable and get the most out of them [23]. To this end, different techniques can be employed, often using both office- and home-based exercises with the device while performing a specific activity for a few hours in different sessions [24, 25, 26].
Besides prescription of LVAs and training on their correct use, VR also contemplates assessment of the home environment, as well as psychological and social worker support. Despite this, it should not be ignored that, according to the Veterans Affairs Low Vision Intervention Trial II (LOVIT II), basic low vision services are sufficient for most people with low vision, although basic services combined with VR programs are most effective for people with a visual acuity of 20/200 or less [27].
VR in AMD patients has largely focused on reading [28] and for this purpose many LVAs have been used. But, today, individuals with AMD demand wider objectives that include, apart for reading, being able to participate in other activities and carry out their daily life and travels independently. If we add to this the fact that modern technologies have greatly expanded access to information for people with low-vision, we get that VR encompass a variety of resources to ultimately fit the person’s goals, needs and demands.
Reading is a sophisticated activity of great importance for the life of the individual in its personal, educational or professional aspects. Conditions compromising the condition of the macula, such as AMD, can greatly affect this ability, which adequate performance largely depends on the reception of central visual information. Depending on the degree to which the scotoma is affected, the reading speed in these patients can be between 25 and 130 words per minute (wpm), while the average reading speed of a person without visual impairment is usually around 200-250 wpm [29].
In everyday life, everyone needs to be able to read texts whose size covers a range from newspaper print to headlines. People with normal vision perform this task with a speed that favors comprehension and comfort. However, AMD patients find that reading speed is compromised as the font size becomes smaller. In general, this population needs magnification of the text to achieve a reading speed that allows them to read effectively, although this will always be lower than that of people without AMD.
In individuals with central field loss (CFL), eccentric fixation is necessary, and the oculomotor pattern differs when reading. Eye movements in people with severe visual impairment tend towards continuous refixation, i.e., fixation stability is weak, and not always stable and functional [30]. Consequently, letter recognition is slower and more difficult [31]. Sometimes, it is difficult to recognize a word with a single fixation, being necessary several saccades within the same word [32]. Visual field loss close to fixation can also affect everyday activities, such as face recognition or shopping [33].
With this in mind, most functional adaptations in these cases are based on training in the use of a preferred retinal locus (PRL) to make eye movements remain in a functional area of the peripheral retina. This PRL is empowered to assume the macular function and thus restore the lost vision-related skills, so assessing its location and characteristics is an essential part of any reading rehabilitation program [34]. In this context, microperimeters offer the most accurate method for PRL assessment (Figure 5).
Microperimetry using a standard grid (52 points) in a study of ranibizumab effects on functional vision in patients with advanced AMD [
The subject’s ability to make visual movements so that the target is held in the PRL correlates with reading speed, as do more intense saccadic movements and stability of fixation [37]. In addition to holding the target on the retina, the eye must move rapidly towards objects further away in the field of vision (saccadic movements). The angle at which the movement to fix the image in the PRL must be made will affect the fixation, the stability of which is crucial for reading and proper perception.
After eccentric viewing training, the location of the retinal area used for fixation may change, but not the fixation stability [38]. Moreover, the person does not always use the same PRL, and may use several depending on the target position. Some authors report that these PRLs may appear untrained in patients in the first six months of disease [38]. Many patients with AMD adopt an PRL on the left area of the scotoma, although more information is obtained from the right area during reading. For this reason, Rubin [39] suggests that it is preferable to use the right area of the scotoma to the left.
The benefits of eccentric viewing training on the reading performance of patients with AMD have been supported by several studies. For example, Nilsson et al. [40] trained 20 patients with neovascular AMD, an absolute central scotoma, and a mean best-corrected visual acuity (BCVA) of 20/475 in the use of a new and more favorable PRL for reading, observing that, after a mean training time of 5.2 hours, 90% of the participants learned to use eccentric viewing, which correlated with a significant improvement in reading speed from 9.0 ± 5.8 words per minute (wpm) to 68.3 ± 19.4 wpm.
A larger sample study evaluating the influence of eccentric viewing training in 242 individuals with a central scotoma concluded that, after an average training time of 3.8 hours, reading speed increased from 48.0 wpm to 71.9 wpm, the size of Arial font that could be read fluently could be reduced from 14.3 to 11.5, the duration of comfortable reading improved from 1.7 to 15.8 min, and the mean percentage of material that was understood by patients could be increased from 73.7 to 92.7% [41].
In addition, when compared with other interventions in the literature, such as a microperimetric biofeedback and microscope teaching program, eccentric viewing training has been found to offer greater benefit in terms of improved reading speed among patients with AMD [42].
It can be said that reading is significantly slower in patients who have not been trained in the use of the retinal locus, but, according to the findings of Watson et al., this does not mean that PRL training should not be further investigated [43].
But different oculomotor pattern is not the only factor that explains the lower reading speed in patients with macular degeneration. Cheong et al. concluded that in patients with AMD the visual processing of letter recognition is also lower, thus negatively influencing reading speed, reading comprehension and enjoyment while reading, as well as resistance in avoiding visual fatigue [44].
Another factor that can determine the efficiency of reading in patients with AMD is the number of characters that can be recognized in each fixation or visual span. This, in addition to the slower visual processing observed in these patients, forces more frequent eye movements. According to Chung [45], training can lengthen the visual lag in normal peripheral vision, although this benefit is less pronounced in older people.
For some researchers, contrast sensitivity is shown to be a critical factor in explaining the future reading efficiency of the patient with AMD over other factors such as scotoma size or BCVA [46]. In general, it can be said that individuals with AMD require contrast enhancement to achieve their optimal reading speed level [47, 48].
Lighting is another key component involved in the reading rehabilitation process for people with AMD, as the negative effect of uncontrolled illumination hinders vision. In this context, it is known that people with AMD often require high levels of illumination [49]. According to Bower et al., [50] at least 2000 lux are necessary to improve reading performance in patients with AMD, although Seiple et al. [51] indicate that this benefit can only be considered for small font sizes.
Finally, it should be pointed out that various studies have tried to establish the degree of importance the way the text is presented has on reading performance in AMD patients.
Chung is one of the researchers who has dedicated her work to this, although she states that there is not enough evidence that typography or text formatting (e.g., page formatting, Rapid Serial Visual Presentation: RSVP, scrolling text) improves reading speed, except in some cases of RSVP [52, 53]. In clinical practice, these are factors that may affect visual comfort and the subjective perception of improved reading or reduced visual fatigue differently from person to person.
Environmental adaptations such as adequate illumination (by the use of light flexes or lecterns) and glare reduction and light with specific wavelengths preferred by the patients (by the use of prescription filters) are two well-known beneficial strategies for improving functional outcome measures in CFL patients.
These interventions result in apparent improved contrast sensitivity and better visual acuity for AMD patients [54, 55], so ensuring these optimal conditions is a fundamental step prior to the prescription of any additional aid.
Increasing the amount of light has demonstrated to have a significant positive effect on sentence reading acuity, reading speed and critical letter size for AMD patients [50].
In addition, some authors who have investigated the effects of making light adjustments in the homes of people with visual impairment have found that higher lighting levels led to greater well-being and a significant improvement in certain instrumental ADLs [56].
The use of filters has also been shown to improve vision-related QoL in patients with AMD, with the success rate of filter placement being better for those patients with visual acuity less than 0.25 and those with advanced AMD [57]. Nevertheless, although various tests exist to determine the best color, tint, lens material or frame type for a given patient, to date no specific protocol has been developed to assist in prescribing tinted or selective transmission lenses [58].
Optical aids for near vision involve the use of lenses to reduce the viewing distance of an object, making it easier to see, and are primarily used to tasks requiring near resolution acuity, such as reading, writing, personal care (i.e., make-up, nail polishing) and different leisure activities, such as sewing or drawing.
These optical LVAs broadly include the use of high-plus reading lenses and different magnifiers (including clip-on, hand-held, or stand devices), which power will ultimately depend on the patient’s remaining vision and on the size of the object or printed material to be seen by the patient [59, 60]. In a consecutive sample of 100 individuals with AMD, these optical LVAs was shown to improve near BCVA from 0.13 (decimal) to 0.39 [61].
When reading with a hand-held magnifier, the magnifier has to move along the line and at the same time keep a constant distance from the text to ensure a clear image [62].
Clip-on magnifiers overcome this disadvantage, but can nevertheless scratch the lenses and reduce the visual field to further distances. In this context, stand magnifiers are the choice preferred by patients, as they offer ergonomic advantages such as a comfortable viewing angle, the possibility of both reading and writing, better illumination, a wider field of view, variable power and magnification, and a greater working distance [63].
Magnification can also be achieved with the use of telescopic devices, which are used to recognize objects that are outside the near vision range. These optical aids can be used for tasks such as reading street signs, road signs, and transport timetables, making them a great ally for outdoor mobility. Furthermore, additional magnifying devices can easily be applied to these devices to improve near vision as well.
In recent years, advances in surgery have allowed intraocular implantation of these devices. Implantable miniature telescopes (IMTs) are visual prosthetic devices usually implanted monocularly depending on the eye with BCVA and, once implanted, are used to magnify objects in the patient’s central visual field and focus them onto healthy areas of the retina, allowing them to recognize objects they would otherwise not be able to see [64]. In this way, the implanted eye is responsible for detailed vision, and the fellow eye will be responsible for peripheral vision tasks, including ambulation.
The safety and efficacy of these devices has been evaluated in different clinical trials that have found similar improvements in BCVA after one year of implantation (≈60% of participants gained three or more lines in either distance or near BCVA), with no serious adverse events reported [65, 66]. In addition, a follow-up study showed that substantial visual improvements achieved with the intervention were maintained at two years [67].
Electronic vision enhancement systems include closed-circuit television (CCTV) systems and other systems incorporating a monitor or a liquid-crystal display (LCD) screen in which the image or the print is projected after being digitized.
These systems provide increased magnification and an enlarged field of view than traditional optical aids, with the possibility of controlling relevant parameters, such as brightness, glare or contrast, so they can be appropriate for individuals which vision is greatly reduced or in which the use of optical aids have failed in achieving their goals.
For example, in a retrospective study of 530 patients with different stages of AMD in which participants were provided with different LVAs, successful VR (reading ability in 94% of patients when only 16% could read before) was achieved with optical visual aids in 58% of patients, whereas 42% needed electronic CCTV systems [68].
A clinical trial in which 37 subjects with central field loss were randomized to receive standard VR (group A = 18 subjects) or standard VR plus electronic magnifiers (group = 19 subjects) showed that, at 1 month, group B read faster and was better at two spot reading tasks such as reading continuous print and finding a number in a phone book, but did not differ from the group A in terms of functional capacity or well-being [69].
In another crossover study comparing the near vision activity performance of 84 experienced users of optical aids when using portable electronic vision enhancement systems plus optical magnifiers or optical magnifiers alone, it was observed that, at 2 months, the use of electronic systems allowed longer duration of reading. In addition, participants reported less difficulty performing a range of near vision activities when using these systems and were able to perform more tasks independently [70].
In addition to CCTV systems, these LVAs include the use of head-mounted displays (HMDs) [71], which enhance vision by coupling digital image processing directly to the patient’s retina, and the use of portable electronic devices (such as tablets, smart-phones and electronic readers), which combine the portability of hand-held magnifiers with the high-resolution displays of electronic magnifiers (CCTV) and incorporate basic features for handling optical characteristics that can be useful to improve functional measures in patients with AMD, such as image enlargement or contrast polarity [72, 73].
Traditionally, VR in AMD patients includes training in eccentric vision and learning to use different optical and electronic magnifiers. However, some authors have recently studied the effects of new strategies, such as Barraza-Bernal et al. [74], who conducted a study with fifteen subjects with normal vision under simulation conditions, showing that PRL can be induced in a specific area by systematic relocation of stimuli.
Similarly, Morales et al. discuss improving the fixation stability in the PRL through biofeedback fixation training (BFT), which consist of slightly moving the gaze towards the training locus during different sessions [75]. Another training paradigm integrating oculomotor control and pattern recognition has also been evaluated, demonstrating that these strategies combined are capable of inducing a PRL over a short period of time in eight subjects with normal vision and a simulated central scotoma [76].
There are several studies that have been carried out to determine the effectiveness of repetitive, perceptual learning as an intervention approach for VR. This approach refers to the improvement in the execution of perceptual tasks as a consequence of training.
Perceptual learning has been found to have neural correlates in visual cortex, which declines with age. Learning effects in older adults are shown to be less than in younger people and are transferred only for the typeface and the retinal location trained. Causes may be a lower visual base span, decreased attention when exercising eccentricity, and less retention of what is learned over time.
People with AMD have a lower visual span, which contributes to a lower peripheral reading speed. According to Legge et al. [77], peripheral reading speed may improve if the size of the peripheral visual span is enlarged, and training based on letter-recognition trials has shown to extend the visual span, contributing to improve reading speed among older adults [78]. These studies [79] were carried out using trigrams, while Bernard et al. [80] sough to find out if a greater benefit can be obtained by using trigrams based on the most commonly used combinations in the English language, determining that the effects of perceptual learning may not be linked to the type of related letters.
Among several studies that have tried to determine the benefits of perpetual learning, some differentiate the way in which texts are presented. Among those using RSVP, there are differences between the vertical and horizontal presentation of text. For example, Yu et al. [81] found that lower speed in vertical presentation corresponds to a decrease in the visual span for vertical reading.
Chung demonstrated that perceptual learning can improve RSVP reading speed in people with AMD after training [82]. Face discrimination and recognition can also be reliably improved in patients with AMD using perceptual learning on face discrimination tasks [83]. Furthermore, Liu et al. [84], who trained people with severe visual impairment (due to different conditions, including AMD) on a visual search task, observed that both search speed and accuracy of the search improved after training, with the improvements being maintained for a period of time at least one month.
Pijnacker et al. [85] proposed to evaluate whether perceptual learning obtains similar results compared to eccentric vision training and oculomotor training, finding in all these interventions effective methods for reading rehabilitation in AMD patients. On the other hand, Seiple et al. [86] supported the efficacy of ocular movement control over eccentric viewing training and RSVP when compared to people with AMD, which does not imply considering the other methods as ineffective.
Digital technologies have improved reading opportunities for AMD patients, first by transferring the text to video screens where it can be manipulated and, more recently, in digital representations that can be personalized [87].
In this sense, several devices that such as CCTVs, tablets, smartphones, or electronic readers have shown a great potential to improve reading ability in individuals with CFL.
One of these technologies whose effectiveness in improving reading between CFL patients has been clinically proven is the iPad (Figure 6). This was demonstrated by a study in which, with the help of the character magnification provided by the iPad, 64 out of 73 patients with AMD (88%) were able to read standard size text (N8) or smaller [88].
Character magnification provided by the iPad [
Another study conducted in 100 patients with low vision (of whom 57 had AMD) found that the iPad offers read speed improvement performance comparable to CCTV systems and home magnification devices, making it a less costly and bulky option for visually impaired people seeking VR [89].
Within this line of work, several applications are being developed for implementation on such devices, such as the MD_evReader application, which scrolls text in a single line to improve reading performance by reducing the demands on the eye movement system and minimising the effects of perceptual crowding [90], proving to reduce reading error rates in individuals with CFL [91].
Modern technologies relevant to VR also include HMDs, which comprise a miniature electronic display in close proximity to one or both eyes which causes a highly magnified virtual image of the miniature screen to appear at a comfortable distance for the viewer. At the present moment, these devices have only demonstrated significant improvements in distance and intermediate visual acuity when compared to conventional optical LVAs in patients with AMD [92], but with the rapid evolution of virtual and augmented reality technologies, innovative approaches are making their way in this field.
For example, in a study which tested the effectiveness of a virtual bioptic telescope and a virtual projection screen implemented with an HMD, improvements in functional ability outcomes estimated from visual information, targets difficulty ratings and reading were observed in a sample of 30 patients with AMD and bilateral central scotomas [93].
Other noteworthy technologies in this area include portable artificial vision devices, such as The OrCam MyEye, which employs a miniature television camera mounted on the frame of the spectacles to recognize text, monetary denominations, faces, and other objects if activated by the patient pressing a trigger button, allowing people with visual impairment to understand text and identify objects through audio feedback. The device, which has recently been commercialized, has proven to be an effective tool for different low-vision patients, leading to contrasted improvements in several visual activities even superior to those achieved with previously used optical aids [94].
There is little scientific evidence of the impact of the use of eccentric viewing on ADLs and safe mobility. Some researchers have determined that development of PRL can occur naturally and that there may even be several PRLs used by the subject [95].
Vukicevic et al. conducted a study with 48 people diagnosed with AMD, aged 60 or over with visual acuity equal to or less than 20/200 (1.0 LogMAR unit) with the aim of investigating the impact of eccentric viewing training on daily self-care activities. To this end, two groups were formed, of which one received eccentric viewing training while the other did not [96]. The results show that even if the subjects had already established their PRL, the execution of daily life tasks improved.
In the case of ADLs, in addition to eccentric viewing training there are other factors that can significantly affect the performance of ADLs, such as lighting, familiarity with the environment, and contrast in materials and surroundings [97].
Illumination is an important method for improving the use of remanent vision, but there are differences between people as to what they consider adequate or comfortable. This is why specialists have to take into account not only the intensity and type of light, but also the surface on which it is to be applied and its position in relation to the subject, adapting it to the preferred viewing area [98].
In other words, being familiar with an environment, with the organization in space of its elements and the appropriate use of lighting can favor the use of PRL, and, hence, the execution of ADLs in an efficient manner.
Liu reviews interventional therapies to improve ADL performance and highlights that patients with AMD can benefit from vision training and the use of optical AVLs, but they need more than that; such as developing skills, using devices or learning problem-solving strategies, so intervention should be multidisciplinary and carried out in multiple sessions to give people enough time to adapt to new devices and skills [99].
Safe mobility for AMD patients is clearly conditioned by the risk of falls, which in the older population can lead to other serious consequences. Displacement in the elderly population is characterized by the involvement of different factors like balance, hearing, reaction capacity and decision-making. From the perspective of vision, the effects on the visual field, contrast sensitivity or the way in which lighting conditions affect the subject are determining factors in how the person will be able to travel [100]. It can be seen that, once again, there are multiple factors involved in the performance of this activity, which implies a multidisciplinary intervention and training in multiple sessions until adaptation to the new skills is achieved.
It is important to properly assess the visual field and information processing in this area in people with low vision, since the processing itself is more complex in detecting objects in the mobile environment while when using the microperimetry test only simple items are detected [101].
Eye and head searching movements when crossing are more difficult in AMD than in normally-sighted people, and there are no stable patterns as in reading. They also involve decision making such as the right time to cross, where the speed of walking among other aspects is crucial for safe movement and good decision making. To this must be add that, as mentioned, the ability to react in older people is diminished. Geruschat et al. confirms that patients with AMD present a higher risk due to increased latency when identifying the right moment to cross a street [102].
The optical devices that patients with AMD mainly use for mobility are telescopes; so are the filters as mentioned above. As for other activities, training and perceptual learning are presented as a decisive factor for the successful rehabilitation of patients with the aim of safe movement.
Although most researchers usually focus on studying eccentric viewing training in individuals with AMD, mainly for reading purposes, it cannot be forgotten that there are many aspects that explain visual functioning for any task. Therefore, research in VR has to consider the multifactorial intervention of characteristics such as the use of eccentric viewing training, the effect of crowding, the improvement of certain visual skills thanks to training during a certain period of time, as well as that of other factors that, although they are currently being studied in depth by authors such as Chung, still need more information to understand their real importance in VR.
Although there are few studies on the transfer of learning and training for reading to other ADLs and mobility, it can be said that visual training guarantees improvements in visual functioning for reading and other tasks, like face discrimination, recognition.
In addition to perceptual learning, oculomotor control and eccentric viewing training, other strategies that may improve reading ability in AMD patients include environmental changes (such as better lighting) and the prescription of filters and optical LVAs, such as high-plus reading lenses and different magnifiers (including clip-on, hand-held, or stand devices). Furthermore, many patients can also benefit from the use of electronic reading aids, including tablets, smartphones, electronic readers, HMDs or CCTV systems.
The widespread presence of accessible portable devices and software has led to a breakthrough in access to information and travel assistance for people with low vision. Some studies are therefore looking at the evidence for the use of such digital devices by the population, in contrast to the use of optical aids.
In fact, there is no such dilemma, because, as initially discussed, AMD patients are increasingly demanding a wider and more varied range of objectives to meet their needs, and the availability of a wider range of resources is only intended to meet these demands.
On the other hand, there are multiple factors involved in the visual skills that a person with AMD must perform, so a greater variety of resources offers the possibility of finding those best suited to their visual conditions.
The authors declare that there is no conflict of interest on the devices or technologies described in this chapter.
ADLs | Activities of Daily Living |
AMD | Age-Related Macular Degeneration |
BCVA | Best-Corrected Visual Acuity |
BFT | Biofeedback Fixation Training |
CCTV | Closed-circuit Television |
CFL | Central Field Loss |
CNV | Choroidal Neovascularization |
GA | Geographic Atrophy |
HMDs | Head Mounted Displays |
IMTs | Implantable Miniature Telescopes |
LCD | Liquid-Crystal Display |
LVAs | Low-Vision Aids |
PRL | Preferred Retinal Locus |
QoL | Quality of Life |
RPE | Retinal Pigment Epithelium |
RSVP | Rapid Serial Visual Presentation |
VEGF | Vascular Endothelial Growth Factor |
VR | Visual Rehabilitation |
WHO | World Health Organization |
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He received a Ph.D. (Magna Cum Laude) in Electrical Engineering in 2002. Since 2017, Dr. Gaiceanu has been a Ph.D. supervisor for students in Electrical Engineering. He has been employed at Dunarea de Jos University of Galati since 1996, where he is currently a professor. Dr. Gaiceanu is a member of the National Council for Attesting Titles, Diplomas and Certificates, an expert of the Executive Agency for Higher Education, Research Funding, and a member of the Senate of the Dunarea de Jos University of Galati. He has been the head of the Integrated Energy Conversion Systems and Advanced Control of Complex Processes Research Center, Romania, since 2016. He has conducted several projects in power converter systems for electrical drives, power quality, PEM and SOFC fuel cell power converters for utilities, electric vehicles, and marine applications with the Department of Regulation and Control, SIEI S.pA. (2002–2004) and the Polytechnic University of Turin, Italy (2002–2004, 2006–2007). He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and cofounder-member of the IEEE Power Electronics Romanian Chapter. He is a guest editor at Energies and an academic book editor for IntechOpen. He is also a member of the editorial boards of the Journal of Electrical Engineering, Electronics, Control and Computer Science and Sustainability. 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He has more than 200 publications in reputed international journals, refereed conference proceedings, and 20 book chapters in books published by internationally renowned publishing houses, such as Springer, CRC press, IGI Global, etc. Currently, he is serving on the editorial board of the prestigious journal Frontiers in Communications and Networks and in the technical program committees of a number of high-ranked international conferences organized by the IEEE, USA, and the ACM, USA. 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Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:null},{id:"226240",title:"Dr.",name:"Andri Irfan",middleName:null,surname:"Rifai",slug:"andri-irfan-rifai",fullName:"Andri Irfan Rifai",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226240/images/7412_n.jpg",biography:"Andri IRFAN is a Senior Lecturer of Civil Engineering and Planning. He completed the PhD at the Universitas Indonesia & Universidade do Minho with Sandwich Program Scholarship from the Directorate General of Higher Education and LPDP scholarship. He has been teaching for more than 19 years and much active to applied his knowledge in the project construction in Indonesia. His research interest ranges from pavement management system to advanced data mining techniques for transportation engineering. He has published more than 50 papers in journals and 2 books.",institutionString:null,institution:{name:"Universitas Internasional Batam",country:{name:"Indonesia"}}},{id:"314576",title:"Dr.",name:"Ibai",middleName:null,surname:"Laña",slug:"ibai-lana",fullName:"Ibai Laña",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314576/images/system/314576.jpg",biography:"Dr. Ibai Laña works at TECNALIA as a data analyst. He received his Ph.D. in Artificial Intelligence from the University of the Basque Country (UPV/EHU), Spain, in 2018. He is currently a senior researcher at TECNALIA. His research interests fall within the intersection of intelligent transportation systems, machine learning, traffic data analysis, and data science. He has dealt with urban traffic forecasting problems, applying machine learning models and evolutionary algorithms. He has experience in origin-destination matrix estimation or point of interest and trajectory detection. Working with large volumes of data has given him a good command of big data processing tools and NoSQL databases. He has also been a visiting scholar at the Knowledge Engineering and Discovery Research Institute, Auckland University of Technology.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"314575",title:"Dr.",name:"Jesus",middleName:null,surname:"L. Lobo",slug:"jesus-l.-lobo",fullName:"Jesus L. Lobo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314575/images/system/314575.png",biography:"Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Artificial Intelligence Research Scientist. In most cases, a project idea or a new research line needs to be investigated to see if it is good enough to take into production or to focus on it. That is exactly what he does, diving into Machine Learning algorithms and technologies to help TECNALIA to decide whether something is great in theory or will actually impact on the product or processes of its projects. So, he is expert at framing experiments, developing hypotheses, and proving whether they’re true or not, in order to investigate fundamental problems with a longer time horizon. He is also able to design and develop PoCs and system prototypes in simulation. He has participated in several national and internacional R&D projects.\n\nAs another relevant part of his everyday research work, he usually publishes his findings in reputed scientific refereed journals and international conferences, occasionally acting as reviewer and Programme Commitee member. Concretely, since 2018 he has published 9 JCR (8 Q1) journal papers, 9 conference papers (e.g. ECML PKDD 2021), and he has co-edited a book. He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:"Polytechnic University of Timişoara",institution:{name:"Polytechnic University of Timişoara",country:{name:"Romania"}}},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:null},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. Science CV available at: https://www.cienciavitae.pt//pt/8E1C-A8B3-78C5 and ORCID: https://orcid.org/0000-0002-0298-3974',institutionString:"University of Lisbon",institution:{name:"Universidade Lusófona",country:{name:"Portugal"}}},{id:"241400",title:"Prof.",name:"Mohammed",middleName:null,surname:"Bsiss",slug:"mohammed-bsiss",fullName:"Mohammed Bsiss",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241400/images/8062_n.jpg",biography:null,institutionString:null,institution:null},{id:"276128",title:"Dr.",name:"Hira",middleName:null,surname:"Fatima",slug:"hira-fatima",fullName:"Hira Fatima",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/276128/images/14420_n.jpg",biography:"Dr. Hira Fatima\nAssistant Professor\nDepartment of Mathematics\nInstitute of Applied Science\nMangalayatan University, Aligarh\nMobile: no : 8532041179\nhirafatima2014@gmal.com\n\nDr. Hira Fatima has received his Ph.D. degree in pure Mathematics from Aligarh Muslim University, Aligarh India. Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. She is a member of Indian Mathematical Society.",institutionString:null,institution:null},{id:"302698",title:"Dr.",name:"Yao",middleName:null,surname:"Shan",slug:"yao-shan",fullName:"Yao Shan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Dalian University of Technology",country:{name:"China"}}},{id:"125911",title:"Prof.",name:"Jia-Ching",middleName:null,surname:"Wang",slug:"jia-ching-wang",fullName:"Jia-Ching Wang",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"National Central University",country:{name:"Taiwan"}}},{id:"357085",title:"Mr.",name:"P. Mohan",middleName:null,surname:"Anand",slug:"p.-mohan-anand",fullName:"P. Mohan Anand",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"356696",title:"Ph.D. Student",name:"P.V.",middleName:null,surname:"Sai Charan",slug:"p.v.-sai-charan",fullName:"P.V. Sai Charan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"357086",title:"Prof.",name:"Sandeep K.",middleName:null,surname:"Shukla",slug:"sandeep-k.-shukla",fullName:"Sandeep K. Shukla",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"356823",title:"MSc.",name:"Seonghee",middleName:null,surname:"Min",slug:"seonghee-min",fullName:"Seonghee Min",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Daegu University",country:{name:"Korea, South"}}},{id:"353307",title:"Prof.",name:"Yoosoo",middleName:null,surname:"Oh",slug:"yoosoo-oh",fullName:"Yoosoo Oh",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:"Yoosoo Oh received his Bachelor's degree in the Department of Electronics and Engineering from Kyungpook National University in 2002. He obtained his Master’s degree in the Department of Information and Communications from Gwangju Institute of Science and Technology (GIST) in 2003. In 2010, he received his Ph.D. degree in the School of Information and Mechatronics from GIST. In the meantime, he was an executed team leader at Culture Technology Institute, GIST, 2010-2012. In 2011, he worked at Lancaster University, the UK as a visiting scholar. In September 2012, he joined Daegu University, where he is currently an associate professor in the School of ICT Conver, Daegu University. Also, he served as the Board of Directors of KSIIS since 2019, and HCI Korea since 2016. From 2017~2019, he worked as a center director of the Mixed Reality Convergence Research Center at Daegu University. From 2015-2017, He worked as a director in the Enterprise Supporting Office of LINC Project Group, Daegu University. His research interests include Activity Fusion & Reasoning, Machine Learning, Context-aware Middleware, Human-Computer Interaction, etc.",institutionString:null,institution:{name:"Daegu Gyeongbuk Institute of Science and Technology",country:{name:"Korea, South"}}},{id:"262719",title:"Dr.",name:"Esma",middleName:null,surname:"Ergüner Özkoç",slug:"esma-erguner-ozkoc",fullName:"Esma Ergüner Özkoç",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Başkent University",country:{name:"Turkey"}}},{id:"419199",title:"Dr.",name:"Qun",middleName:null,surname:"Yang",slug:"qun-yang",fullName:"Qun Yang",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Auckland",country:{name:"New Zealand"}}},{id:"351158",title:"Prof.",name:"David W.",middleName:null,surname:"Anderson",slug:"david-w.-anderson",fullName:"David W. Anderson",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Calgary",country:{name:"Canada"}}},{id:"351159",title:"BSc.",name:"Kalum J.",middleName:null,surname:"Ost",slug:"kalum-j.-ost",fullName:"Kalum J. Ost",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Calgary",country:{name:"Canada"}}},{id:"325029",title:"Dr.",name:"Prem Chand",middleName:null,surname:"Jain",slug:"prem-chand-jain",fullName:"Prem Chand Jain",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Shiv Nadar University",country:{name:"India"}}},{id:"357275",title:"Dr.",name:"Thomas",middleName:null,surname:"Mih",slug:"thomas-mih",fullName:"Thomas Mih",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Buea",country:{name:"Cameroon"}}},{id:"305305",title:"Dr.",name:"Arturo Yosimar",middleName:null,surname:"Jaen-Cuellar",slug:"arturo-yosimar-jaen-cuellar",fullName:"Arturo Yosimar Jaen-Cuellar",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Autonomous University of Queretaro",country:{name:"Mexico"}}},{id:"305315",title:"Dr.",name:"David Alejandro",middleName:null,surname:"Elvira-Ortiz",slug:"david-alejandro-elvira-ortiz",fullName:"David Alejandro Elvira-Ortiz",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Autonomous University of Queretaro",country:{name:"Mexico"}}},{id:"344374",title:"Dr.",name:"Manuel",middleName:null,surname:"Toledano-Ayala",slug:"manuel-toledano-ayala",fullName:"Manuel Toledano-Ayala",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Autonomous University of Queretaro",country:{name:"Mexico"}}}]}},subseries:{item:{id:"27",type:"subseries",title:"Multi-Agent Systems",keywords:"Collaborative Intelligence, Learning, Distributed Control System, Swarm Robotics, Decision Science, Software Engineering",scope:"Multi-agent systems are recognised as a state of the art field in Artificial Intelligence studies, which is popular due to the usefulness in facilitation capabilities to handle real-world problem-solving in a distributed fashion. The area covers many techniques that offer solutions to emerging problems in robotics and enterprise-level software systems. Collaborative intelligence is highly and effectively achieved with multi-agent systems. Areas of application include swarms of robots, flocks of UAVs, collaborative software management. Given the level of technological enhancements, the popularity of machine learning in use has opened a new chapter in multi-agent studies alongside the practical challenges and long-lasting collaboration issues in the field. It has increased the urgency and the need for further studies in this field. We welcome chapters presenting research on the many applications of multi-agent studies including, but not limited to, the following key areas: machine learning for multi-agent systems; modeling swarms robots and flocks of UAVs with multi-agent systems; decision science and multi-agent systems; software engineering for and with multi-agent systems; tools and technologies of multi-agent systems.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/27.jpg",hasOnlineFirst:!1,hasPublishedBooks:!1,annualVolume:11423,editor:{id:"148497",title:"Dr.",name:"Mehmet",middleName:"Emin",surname:"Aydin",slug:"mehmet-aydin",fullName:"Mehmet Aydin",profilePictureURL:"https://mts.intechopen.com/storage/users/148497/images/system/148497.jpg",biography:"Dr. Mehmet Emin Aydin is a Senior Lecturer with the Department of Computer Science and Creative Technology, the University of the West of England, Bristol, UK. His research interests include swarm intelligence, parallel and distributed metaheuristics, machine learning, intelligent agents and multi-agent systems, resource planning, scheduling and optimization, combinatorial optimization. Dr. Aydin is currently a Fellow of Higher Education Academy, UK, a member of EPSRC College, a senior member of IEEE and a senior member of ACM. In addition to being a member of advisory committees of many international conferences, he is an Editorial Board Member of various peer-reviewed international journals. 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Moreover, in the field of machine learning, evolutionary computation has carved out a significant niche both in the generation of learning models and in the automatic design and optimization of hyperparameters in deep learning models. This collection aims to include quality volumes on various topics related to evolutionary algorithms and, alternatively, other metaheuristics of interest inspired by nature. For example, some of the issues of interest could be the following: Advances in evolutionary computation (Genetic algorithms, Genetic programming, Bio-inspired metaheuristics, Hybrid metaheuristics, Parallel ECs); Applications of evolutionary algorithms (Machine learning and Data Mining with EAs, Search-Based Software Engineering, Scheduling, and Planning Applications, Smart Transport Applications, Applications to Games, Image Analysis, Signal Processing and Pattern Recognition, Applications to Sustainability).",coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",keywords:"Genetic Algorithms, Genetic Programming, Evolutionary Programming, Evolution Strategies, Hybrid Algorithms, Bioinspired Metaheuristics, Ant Colony Optimization, Evolutionary Learning, Hyperparameter Optimization"},{id:"26",title:"Machine Learning and Data Mining",scope:"The scope of machine learning and data mining is immense and is growing every day. It has become a massive part of our daily lives, making predictions based on experience, making this a fascinating area that solves problems that otherwise would not be possible or easy to solve. This topic aims to encompass algorithms that learn from experience (supervised and unsupervised), improve their performance over time and enable machines to make data-driven decisions. It is not limited to any particular applications, but contributions are encouraged from all disciplines.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/26.jpg",keywords:"Intelligent Systems, Machine Learning, Data Science, Data Mining, Artificial Intelligence"},{id:"27",title:"Multi-Agent Systems",scope:"Multi-agent systems are recognised as a state of the art field in Artificial Intelligence studies, which is popular due to the usefulness in facilitation capabilities to handle real-world problem-solving in a distributed fashion. 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We welcome chapters presenting research on the many applications of multi-agent studies including, but not limited to, the following key areas: machine learning for multi-agent systems; modeling swarms robots and flocks of UAVs with multi-agent systems; decision science and multi-agent systems; software engineering for and with multi-agent systems; tools and technologies of multi-agent systems.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/27.jpg",keywords:"Collaborative Intelligence, Learning, Distributed Control System, Swarm Robotics, Decision Science, Software Engineering"}],annualVolumeBook:{},thematicCollection:[],selectedSeries:{title:"Artificial Intelligence",id:"14"},selectedSubseries:null},seriesLanding:{item:{id:"7",title:"Biomedical Engineering",doi:"10.5772/intechopen.71985",issn:"2631-5343",scope:"Biomedical Engineering is one of the fastest-growing interdisciplinary branches of science and industry. 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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,institution:{name:"University of Silesia",institutionURL:null,country:{name:"Poland"}}},subseries:[{id:"7",title:"Bioinformatics and Medical Informatics",keywords:"Biomedical Data, Drug Discovery, Clinical Diagnostics, Decoding Human Genome, AI in Personalized Medicine, Disease-prevention Strategies, Big Data Analysis in Medicine",scope:"Bioinformatics aims to help understand the functioning of the mechanisms of living organisms through the construction and use of quantitative tools. The applications of this research cover many related fields, such as biotechnology and medicine, where, for example, Bioinformatics contributes to faster drug design, DNA analysis in forensics, and DNA sequence analysis in the field of personalized medicine. Personalized medicine is a type of medical care in which treatment is customized individually for each patient. Personalized medicine enables more effective therapy, reduces the costs of therapy and clinical trials, and also minimizes the risk of side effects. Nevertheless, advances in personalized medicine would not have been possible without bioinformatics, which can analyze the human genome and other vast amounts of biomedical data, especially in genetics. The rapid growth of information technology enabled the development of new tools to decode human genomes, large-scale studies of genetic variations and medical informatics. 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Recently, bioinspired systems have been successfully employing biomechanics to develop and improve assistive technology and rehabilitation devices. The research topic "Bioinspired Technology and Biomechanics" welcomes studies reporting recent advances in bioinspired technologies that contribute to individuals\' health, inclusion, and rehabilitation. 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Chapters exploring biomaterial approaches such as polymer synthesis and characterization, drug and gene vector design, biocompatibility, immunology and toxicology, and self-assembly at the nanoscale, are welcome. 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