Technological developments have resulted in tremendous increases in the volume and diversity of the data and information that must be processed in the course of biomedical and clinical research and practice. Researchers are at the same time under ever greater pressure to share data and to take steps to ensure that data resources are interoperable. The use of ontologies to annotate data has proven successful in supporting these goals and in providing new possibilities for the automated processing of data and (...) information. In this chapter, we describe different types of vocabulary resources and emphasize those features of formal ontologies that make them most useful for computational applications. We describe current uses of ontologies and discuss future goals for ontology-based computing, focusing on its use in the field of infectious diseases. We review the largest and most widely used vocabulary resources relevant to the study of infectious diseases and conclude with a description of the Infectious Disease Ontology (IDO) suite of interoperable ontology modules that together cover the entire infectious disease domain. (shrink)

Over 60% of all epidemics have a zoonotic origin, that is, they result from the transmission of infectious diseases from animals to humans. The spill-over of diseases often happens because humans exploit and use animals. In this article, I outline the four most common interfaces that favour the emergence and spread of zoonotic infectious diseases: wildlife hunting, small-scale farming, industrialised farming practices and live animal markets. I analyse which practices serve human food security – and thus have a non-trivial purpose (...) – and which predominantly have an economic purpose or serve as a symbol of wealth. I conclude that many practices that increase the risk for zoonotic infectious disease outbreaks actually do not contribute to the survival and food security of humans. I make two arguments in turn. First, I argue that in cases where the consumption and use of animal products does not contribute to the food security of a population, then this population has a duty to abstain from them, since they impose a grave and avoidable risk to themselves as well as to innocent third-parties. However, some communities must sometimes rely on practices that increase the risk of emergence and transmission of zoonotic infectious diseases, because they have no healthy alternatives. That is, the food security of the local population depends on the consumption and use of risky animal products. The second argument I advance is that, in such scenarios, the international community has a duty to provide the communities concerned with alternative food options, as well as economic and educational opportunities and technologies, in order to reduce the spill-over risk of infectious diseases. Given that abstention from such practices contributes signifcantly to the public good and benefits the international community, the latter has a corresponding duty to provide local communities which abandon such practices with alternatives. (shrink)

Data indicate the ubiquity and rapid increase of depression wherever war, want and social upheaval are found. The goal of this paper is to clarify such claims and draw conceptual distinctions separating the depressive states that are pathological from those that are normal and normative responses to misfortune. I do so by appeal to early modern writing on melancholy by Robert Burton, where the inchoate and boundless nature of melancholy symptoms are emphasized; universal suffering is separated from the disease (...) states known as melancholy or melancholia, and normal temperamental variation is placed in contrast to such disease states. In Burton's time these distinctions and characterizations could be secured by the anchoring tenets of humoral theory. Without such anchoring, and in light of the findings and assumptions of today's biological diagnostic psychiatry, we must re-visit each of them. My goals here are to show the need for analytic foundations when claims are made about depression such as those cited above, and to draw attention to some contemporary attempts that may help provide those foundations, particularly, attempts to define disorder or disease. With adjustments, one of these (Cooper 2002) is shown to take us some way toward that goal. (shrink)

The ongoing COVID-19 pandemic has brought science to the fore of public discourse and, considering the complexity of the issues involved, with it also the challenge of effective and informative science communication. This is a particularly contentious topic, in that it is both highly emotional in and of itself; sits at the nexus of the decision-making process regarding the handling of the pandemic, which has effected lockdowns, social behaviour measures, business closures, and others; and concerns the recording and reporting of (...) disease mortality. To clarify a point that has caused much controversy and anger in the public debate, the first part of the present article discusses the very fundamentals underlying the issue of causative attribution with regards to mortality, lays out the foundations of the statistical means of mortality estimation, and concretizes these by analysing the recording and reporting practices adopted in England and their widespread misrepresentations. The second part of the article is empirical in nature. I present data and an analysis of how COVID-19 mortality has been reported in the mainstream media in the UK and the USA, including a comparative analysis both across the two countries as well as across different media outlets. The findings clearly demonstrate a uniform and worrying lack of understanding of the relevant technical subject matter by the media in both countries. Of particular interest is the finding that with a remarkable regularity (????>0.998), the greater the number of articles a media outlet has published on COVID-19 mortality, the greater the proportion of its articles misrepresented the disease mortality figures. (shrink)

COVID-19 began in China in December 2019. As of January 2021, over a hundred million instances had been reported worldwide, leaving a deep socio-economic impact globally. Current investigation studies determined that artificial intelligence (AI) can play a key role in reducing the effect of the virus spread. The prediction of COVID-19 incidence in different countries and territories is important because it serves as a guide for governments, healthcare providers, and the general public in developing management strategies to battle the (...) class='Hi'>disease. The prediction proved beneficial in the early months of 2020 to alert nations and territories in danger of an outbreak, allowing them to take preventative measures. Despite the fact that the COVID-19 outbreak has expanded to practically every location on the planet, the prediction has value in terms of monitoring the intensity of the spread and recovery, as well as determining the likelihood of a sequel or tertiary epidemic. COVID-19, like influenza, could become a seasonal or recurring epidemic in the future. COVID-19 activity must so be predicted and monitored now and in the future. (shrink)

During the recent Ebola epidemic, some commentators and stakeholders argued that it would be unethical to carry out a study that withheld a potential treatment from affected individuals with such a serious, untreatable disease. As a result, the initial trials of experimental treatments did not have control arms, despite important scientific reasons for their inclusion. In this paper, we consider whether the duty to rescue entails that it would be unethical to withhold an experimental treatment from patient-participants with (...) serious diseases for which there are no effective treatments, even when doing so is scientifically necessary to test the effectiveness of the treatment. We argue that the duty to rescue will rarely apply. The context of medical research also throws new light on the content of the duty to rescue, since the interests of future patients—who stand to benefit from the fruits of medical research—are relevant to whether the duty applies. (shrink)

The present article is presenting the ‘Healthcare Hazards and Its Impact on Health Insurance Business – An Overview during COVID-19’. The present paper studied the health insurance, health insurance plans in India, Indian market size, health care industry, government actions for the COVID-19, and healthcare business in India, private health insurance in India, hazardous of the healthcare industry and health insurances, and Indian healthcare issues in 2019. The author has concluded that all insurance policies are levied higher taxes by the (...) government, these lead higher income to the companies, and these are creating how commissions to the agents and other insurance organizations under reinsurance, but no benefits to the insured. It may not be a long term benefit, why because there is no maturity fund/income, because of these are shortterm benefits; how many of the policyholders are getting the benefits from the general health insurance companies. Hence, the research is required to calculate for the need of levy-the tax from the non-claimant portion of the income of the general health insurance on an annual basis to the health department of the nation. (shrink)

Concerns about emerging and re-emerging infectious diseases have given a new lease of life to quarantinist measures: a series of time-honoured techniques for controlling the spread of infectious diseases through breaking the chain of human contagion. Since such measures typically infringe individual rights or privacy their use is subject to legal regulations and gives rise to ethical and political worries and suspicions. Yet in some circumstances they can be very effective. After considering some case studies that show how epidemics are (...) unique, fluid and affected by a multitude of contingent factors, it is argued that the legal and ethical guidelines may not always be the best approach to discipline the use of quarantinist measures. An alternative model based on ex-post political accountability for reasonableness is proposed. This model restores the centrality of political decision and expert judgement in situations characterized by high risk, uncertainty and contingency. It is argued that such alternative model affords quicker and more flexible responses to serious outbreaks of infections, while providing adequate protection against abuses. (shrink)

As a response to the opioid epidemic in the United States, the Centers for Disease Control and Prevention (CDC) published the CDC Guideline for Prescribing Opioids for Chronic Pain in 2016. This document served as a means to reduce risks and address harms of opioid use by recommending that clinicians conduct periodic urine drug testing for patients on chronic opioid therapy. As an unintended result of this recommendation, providers began using unexpected urine drug test results as a reason (...) to dismiss patients from practice, both out of concern for their patients’ wellbeing as well as their own legal risks. Using Husserl’s and Heidegger’s phenomenology, we argue that this science-based, black-and-white practice does not heed the patient as a whole person. Instead, we recommend a more contextual, patient-centered approach that can help us to better understand and manage patient needs in such contexts. (shrink)

Diabetes is a major public health issue that affects the nations of our time to a large extent and is described as a non-communicable epidemic. Diabetes mellitus is a common disease where there is too much sugar (glucose) floating around in your blood. This occurs because either the pancreas can’t produce enough insulin or the cells in body have become resistant to insulin. The concentration in this paper is on diagnosis diabetes by designing a proposed expert system. The (...) main goal of this expert system is to get the appropriate diagnosing of the illness, dealing with it quickly, and tips for permanent treatment whenever possible is given out. SL5 object expert system language was used for designing and implementing the proposed expert system. (shrink)

Digital data help data scientists and epidemiologists track and predict outbreaks of disease. Mobile phone GPS data, social media data, or other forms of information updates such as the progress of epidemics are used by epidemiologists to recognize disease spread among specific groups of people. Targeting groups as potential carriers of a disease, rather than addressing individuals as patients, risks causing harm to groups. While there are rules and obligations at the level of the individual, we have (...) to reach a stage in the development of data analytics where groups are protected as entities. This chapter offers a deeper examination of harms to the groups. (shrink)

Background: The epidemic scourge of rickets in the 19th century was caused by vitamin D deficiency due to inadequate sun exposure and resulted in growth retardation, muscle weakness, skeletal deformities, hypocalcemia, tetany, and seizures. The encouragement of sensible sun exposure and the fortification of milk with vitamin D resulted in almost complete eradication of the disease. Objectives: this paper is going to resolve the exiting problems of rickets by correctly diagnosing and offering the proper treatment. Methods: In this (...) paper, we present an expert system for rickets diagnosis which will helps doctors to explore everything related to the problems of rickets. We look forward to offer simplified answers to most of the rickets disease. (shrink)

This paper aims to analyze the ethical challenges in experimental drug use during the early stage of the COVID-19 pandemic, using Germany as a case study. In Germany uniform ethical guidelines were available early on nationwide, which was considered as desirable by other states to reduce uncertainties and convey a message of unity. The purpose of this ethical analysis is to assist the preparation of future guidelines on the use of medicines during public health emergencies. The use of hydroxychloroquine, remdesivir (...) and COVID-19 convalescent plasma in clinical settings was analyzed from the perspective of the ethical principles of beneficence, non-maleficence, justice and autonomy. We observed that drug safety and drug distribution during the pandemic affects all four ethical principles. We therefore recommend to establish ethical guidelines (i) to discuss experimental treatment options with patients from all population groups who are in urgent need, (ii) to facilitate the recording of patient reactions to drugs in off-label use, (iii) to expand inclusion criteria for clinical studies to avoid missing potentially negative effects on excluded groups, and (iv) to maintain sufficient access to repurposed drugs for patients with prior conditions. (shrink)

Influenza virus (H1N1) caused seasonal influenza, is an acute respiratory infection that spreads to whole worldwide. The first case of influenza A virus pandemics in India came to light in May 2009 in Hyderabad city of Telangana. Human-to-human transmission led to considerable morbidity and mortality within the country until December.The total number of seasonal influenza cases in India from the year 2010 to 31st July 2020 is 1,73,488. Decreasing ambient temperature is often associated with influenza weather. The viral particle's ability (...) to survive long term in cold temperatures also plays an important role. Besides, coagulation during winter serves as a co-contributing factor in facilitating the spread of the influenza virus. The environmental temperature leads to physical stress and energy loss due to thermal regulation, which weakens the immune system and thereby increases the host's likelihood of infection. The prevention of epidemics in India was possible only by quick and efficient measures taken by the Government.Soon after cases were registered at Pune, Maharashtra, and other places across the country, steps were taken to revise the guidelines for the control of the disease in India.Classification of cases in health facilities and home environments, classification of cases, providing treatment to appropriate persons, public education, and other appropriate measures proved to be very effective in due course of time. In this paper, we discussed the total cases and mortality due to seasonal influenza virus in the states and union territories in India from the year 2010 to the year 2020. (shrink)

Taking people’s longevity as a measure of good life, humankind can proudly say that the average person is living a much longer life than ever before. The AIDS epidemic has however for the first time in decades stalled and in some cases even reverted this trend in a number of countries. Climate change is increasingly becoming a major challenge for food security and we can anticipate that hunger caused by crop damages will become much more common. -/- Since many (...) of the challenges humanity faced in the past were overcome by inventive solutions coming from the life sciences, we are compelled to reconsider how we incentivize science and technology development so that those in need can benefit more broadly from scientific research. There is a huge portion of the world population that is in urgent need for medicines to combat diseases that are currently neglected by the scientific community and could immensely benefit from agricultural research that specifically targets their environmental conditions. At the same time efforts have to be made to make the fruits of current and future research more widely accessible. These changes would have to be backed by a range of moral arguments to attract people with diverging notions of global justice. This article explores the main ethical theories used to demand a greater share in the benefits from scientific progress for the poor. Since life sciences bring about a number of special concerns, a short list of conflictive issues is also offered. (shrink)

The Hippocratic Oath is a code of ethics defining correct behaviour by physicians they are required to commit themselves to before being accepted into the profession. It was the first code of ethics for any profession. While originating in Ancient Greece, it subsequently evolved, but the current code still embodies many of the core injunctions of the original code. The most widely accepted current form is the 2006 The Declaration of Geneva by the World Medical Association to be taken before (...) being admitted as a member of the medical profession. The most important of its injunctions are: ‘The health of my patient will be my first consideration’ and ‘I will maintain the utmost respect for human life’. The first is a rewording of the injunction from Epidemics, Book I, of the Hippocratic school: ‘Practice two things in your dealings with disease: either help or do not harm the patient.’ This was later simplified to the most basic precept of the Hippocratic Oath: ‘First, do no harm.’ It is one of the principal precepts of bioethics that all students in healthcare that, given an existing problem, it may be better not to do something, or even to do nothing, than to risk causing more harm than good. The development of neurotechnology could be subsumed with little modification under the Geneva formulation of the Hippocratic Oath, extending this precept to a commitment not to damage people’s psychological health. (shrink)

This article proposes that, in line with moral-cosmopolitan theorists, affluent nations have an obligation, founded in justice and not merely altruism or beneficence, to share the responsibility of the burden of public health implementation in low-income contexts. The current Ebola epidemic highlights the fact that countries with under-developed health systems and limited resources cannot cope with a significant and sudden health threat. The link between burden of disease, adverse factors in the social environment and poverty is well established (...) and confirmed by the 2008 World Health Organization (WHO)’s Social Determinants of Health Commission report. Well-resourced nations generally consider that they have some humanitarian obligation to assist where possible, but this obligation is limited. The following questions are considered: Is reliance on the principle of beneficence to address the global disparities in the social determinants of health and life expectancy at birth good enough? Do well-resourced nations have some obligation from justice, which is stronger than from beneficence, and which cannot be as easily cast aside or diminished, to address these issues? In a globalised world, shaped by centuries of historical injustice and where first-world economies are now so intertwined and reliant on third-world labour, beneficence is not a strong enough principle on which to base an obligation to achieve the WHO vision of ‘health equity through action on the social determinants of health’. (shrink)

Background: A better understanding of the pattern of epidemic-related referrals to healthcare centers might allow the identification of vulnerabilities and the required changes that the healthcare management system should undergo. Objectives: This study aimed to investigate the COVID-19 referral pattern and the role of media and health management planning in changing the trends. Methods: Data extracted from the electronic medical database of Imam Khomeini Hospital Complex (IKHC), located in Tehran, Iran, from February 20 to June 4, 2020 were examined. (...) Individuals were divided into two groups, COVID-19 positive and negative. We used Google Trends to evaluate Google Internet search queries and also available policy documents, programs, and official news related to COVID-19 in Iran during the mentioned period. Results: In this study, 8647 individuals aged 46.05 ± 16.5 years were referred to IKHC. Approximately 57% were male, and 70% were COVID-19 positive. The most clinical symptoms were dyspnea, fever, cough, and myalgia. Chronic kidney disease (CKD) and type 2 diabetes mellitus were the most common underlying health conditions. In the first two weeks, the percentage of negative cases was higher than positive cases and then the pattern was reversed, when people searched for information about COVID-19 in media. Conclusions: Proper and timely information and education to people through the media and health management measures can be effective in reducing unnecessary visits to health centers, preventing the exhaustion of medical staff, and controlling the disease during epidemics. (shrink)

The conceptions of lovesickness and of its remedies that emerge in the Decameron result from a medical tradition that in previous centuries was assimilated by the Latin culture. The case of the Decameron is particularly interesting because this work was composed during the Black Death epidemic, between 1348 and 1354. Boccaccio’s Decameron seems to be situated in a tension between two diseases: the black plague, from which the brigata tries to escape, and lovesickness. It is quite significant that Boccaccio (...) dedicated his work to women who love and need the comfort of literature, thereby addressing a new ideal of noble women, not based on their wealth, but on their intelligence and sensitivity. Women are often victims of their melancholy, because they have no opportunity to distract themselves, being confined to the private space of their rooms. Boccaccio describes women as being subject to passion and illness, so that the lovesickness cases described in the Decameron strongly allude to the discrimination of women and to the oppression they had to endure. An explicative example that testifies to the preeminent role that the medical culture played is Decameron X, 7, in which Lisa, the daughter of an apothecary, strangely cannot be healed by pharmacological remedies that her father knows, and not a single physician can help to heal her lovesickness. The case of Lisa can be interpreted as an exemplum: a woman afflicted by the same sickness as Lisa could understand how to behave by means of reading of this novella. Moreover, this paper will demonstrate that a useful outline of Lisa’s symptomatology can be found in Dino del Garbo’s commentary on Guido Cavalcanti’s poem Donna me prega. (shrink)

This book analyses three of the most prevalent illnesses of late modernity: anxiety, depression and Alzheimer’s disease, in terms of their relation to cultural pathologies of the social body. Usually these conditions are interpreted clinically in terms of individualized symptoms and responded to discretely, as though for the most part unrelated to each other. However, these diseases also have a social and cultural profile that transcends their particular symptomologies and etiologies. Anxiety, depression and Alzheimer’s are diseases related to disorders (...) of the collective esprit de corps of contemporary society. Multidisciplinary in approach, the book addresses questions of how these conditions are manifest at both the individual and collective levels in relation to hegemonic biomedical and psychologistic understandings. Rejecting such reductive diagnoses, the authors argue that anxiety, depression and Alzheimer’s disease, as well as other contemporary epidemics, are to be analysed in the light of individual and collective experiences of profound and radical changes in our civilization. A diagnosis of our times, Late Modern Subjectivity and its Discontents will appeal to a broad range of scholars with interests in health and illness, the sociology of medicine and contemporary life. (shrink)

The viruses coexist for approx. 300 million years with the humans. Sometimes viruses can infect people on a large scale. But how was the current pandemic possible? Global warming is causing extreme weather events that have led to an increase in infectious diseases. The new climate can support epidemiological vectors for longer periods of time, creating more favorable conditions for replication and the emergence of new vectors. In the case of emerging infectious diseases, it is considered that there is a (...) border that has already been crossed. Viruses normally have a native area (their "reservoir") from which they should not be pushed out. This creates a dangerous intimacy, with "hotspots" that include locations such as markets, which become real hotbeds of epidemics. DOI: 10.13140/RG.2.2.26974.87364 . (shrink)

_La Peste_, originally published in 1947 by the Nobel Prize-winning writer Albert Camus, chronicles the progression of deadly bubonic plague as it spreads through the quarantined Algerian city of Oran. While most discussions of fictional examples within aesthetics are either historical or hypothetical, Camus offers an example of "pestilence fiction." Camus chose fiction to convey facts--about plagues in the past, his own bout with tuberculosis at age seventeen, living under quarantine away from home for several years, and forced separation from (...) his wife who remained in Algiers while he was abroad in Nazi-occupied France. His own lived experiences undergird an imaginative account of shared human realities with which we can identify: vulnerability to the disease, isolation, fear, and finally humanitarianism. _The Plague_ teaches us to neither covet nor expect what we so casually took for granted. This collection of original essays on philosophical themes in _The Plague_ is of special relevance during and in the aftermath of Covid-19 but also provides reflections that will be of lasting value to those interested in this classic work of literature. The novel explores questions of enduring importance. Do we collectively meet the threshold of ethical behavior posed by Camus who wrote, "What's true of all the evils in the world is true of plague as well. It helps men to rise above themselves"? Or does the absurd undermine the compassionate? Do "heroes" dutifully fight a plague with "common decency," or does human nature resign itself to the normalization of uncontrollable suffering and death? There are myriad ways to approach the novel and this volume encourages readers to ponder human dilemmas in fictional Oran informed by our current pandemic. Series editor forward by Richard Eldridge. List of Contributors includes Steven G. Kellman, Jane E. Schultz, Andrew Edgar, Kathleen Higgins, Edward B. Weiser, Cynthia A. Freeland, and Margaret E. Gray; see "Introduction" by Peg Brand Weiser below. (shrink)

This contribution gives an overview of the few passages of Ancient Greek literature dealing with the causes of epidemics and contagions (i.e. in Hippocrates, Thucydides, Isocrates, ps-Aristotle’s Problems, Plutarch, and Galen). With the help of the distinction between an ontological and a physiological conception of what a disease is, I suggest that the latter was an obstacle to better understand the process through which epidemics spread. I nonetheless show that the ontological conception of these diseases was not entirely absent (...) from Antiquity, as it is shown by Galen, who offers an etiological explanation of the origin of epidemics that combines both conceptions, the ontological and the physiological one. (shrink)

The Neurological Disease Ontology (ND) is being developed to provide a comprehensive framework for the representation of neurological diseases (Diehl et al., 2013). ND utilizes the model established by the Ontology for General Medical Science (OGMS) for the representation of entities in medicine and disease (Scheuermann et al., 2009). The goal of ND is to include information for each disease concerning its molecular, genetic, and environmental origins, the processes involved in its etiology and realization, as well as (...) its clinical presentation including signs and symptoms. (shrink)

Many epidemics consist in individuals spreading infection to others. From the population perspective, they also have population characteristics important in modeling, explaining, and intervening in epidemics. I analyze epidemiology’s contemporary population perspective through the example of epidemics by examining two central principles attributed to Geoffrey Rose: a distinction between the causes of cases and the causes of incidence, and between “high-risk” and “population” strategies of prevention. Both principles require revision or clarification to capture the sense in which they describe distinct (...) perspectives on the same phenomenon, each perspective capturing a different level of contrastive analysis. (shrink)

Rare diseases pose a particular priority setting problem. The UK gives rare diseases special priority in healthcare priority setting. Effectively, the National Health Service is willing to pay much more to gain a quality-adjusted life-year related to a very rare disease than one related to a more common condition. But should rare diseases receive priority in the allocation of scarce healthcare resources? This article develops and evaluates four arguments in favour of such a priority. These pertain to public values, (...) luck egalitarian distributive justice the epistemic difficulties of obtaining knowledge about rare diseases and the incentives created by a higher willingness to pay. The first is at odds with our knowledge regarding popular opinion. The three other arguments may provide a reason to fund rare diseases generously. However, they are either overinclusive because they would also justify funding for many non-rare diseases or underinclusive in the sense of justifying priority for only some rare diseases. The arguments thus fail to provide a justification that tracks rareness as such. There are no data in this work. (shrink)

Abstract: Heart diseases are increasing daily at a rapid rate and it is alarming and vital to predict heart diseases early. The diagnosis of heart diseases is a challenging task i.e. it must be done accurately and proficiently. The aim of this study is to determine which patient is more likely to have heart disease based on a number of medical features. We organized a heart disease prediction model to identify whether the person is likely to be diagnosed (...) with a heart disease or not using the medical features of the person. We used many different algorithms of machine learning such as Gaussian Mixture, Nearest Centroid, MultinomialNB, Logistic RegressionCV, Linear SVC, Linear Discriminant Analysis, SGD Classifier, Extra Tree Classifier, Calibrated ClassifierCV, Quadratic Discriminant Analysis, GaussianNB, Random Forest Classifier, ComplementNB, MLP Classifier, BernoulliNB, Bagging Classifier, LGBM Classifier, Ada Boost Classifier, K Neighbors Classifier, Logistic Regression, Gradient Boosting Classifier, Decision Tree Classifier, and Deep Learning to predict and classify the patient with heart disease. A quite helpful approach was used to regulate how the model can be used to improve the accuracy of prediction of heart diseases in any person. The strength of the proposed model was very satisfying and was able to predict evidence of having a heart disease in a particular person by using Deep Learning and Random Forest Classifier which showed a good accuracy in comparison to the other used classifiers. The proposed heart disease prediction model will enhances medical care and reduces the cost. This study gives us significant knowledge that can help us predict the person with heart disease. The dataset was collected from Kaggle depository and the model is implemented using python. (shrink)

Abstract: Heart diseases are increasing daily at a rapid rate and it is alarming and vital to predict heart diseases early. The diagnosis of heart diseases is a challenging task i.e. it must be done accurately and proficiently. The aim of this study is to determine which patient is more likely to have heart disease based on a number of medical features. We organized a heart disease prediction model to identify whether the person is likely to be diagnosed (...) with a heart disease or not using the medical features of the person. We used many different algorithms of machine learning such as Gaussian Mixture, Nearest Centroid, MultinomialNB, Logistic RegressionCV, Linear SVC, Linear Discriminant Analysis, SGD Classifier, Extra Tree Classifier, Calibrated ClassifierCV, Quadratic Discriminant Analysis, GaussianNB, Random Forest Classifier, ComplementNB, MLP Classifier, BernoulliNB, Bagging Classifier, LGBM Classifier, Ada Boost Classifier, K Neighbors Classifier, Logistic Regression, Gradient Boosting Classifier, Decision Tree Classifier, and Deep Learning to predict and classify the patient with heart disease. A quite helpful approach was used to regulate how the model can be used to improve the accuracy of prediction of heart diseases in any person. The strength of the proposed model was very satisfying and was able to predict evidence of having a heart disease in a particular person by using Deep Learning and Random Forest Classifier which showed a good accuracy in comparison to the other used classifiers. The proposed heart disease prediction model will enhances medical care and reduces the cost. This study gives us significant knowledge that can help us predict the person with heart disease. The dataset was collected from Kaggle depository and the model is implemented using python. (shrink)

The early Stoics diagnose vicious agents with various psychological diseases, e.g. love of money and love of wine. Such diseases are characterized as false evaluative opinions that lead the agent to form emotional impulses for certain objects, e.g. money and wine. Scholars have therefore analyzed psychological diseases simply as dispositions for assent. This interpretation is incomplete, I argue, and should be augmented with the claim that psychological disease also affects what kind of action-guiding impressions are created prior to giving (...) assent. This proposal respects the Stoic insistence that impression-formation, no less than assent, is an activity of reason. In so far as the wine-lover’s reason is corrupted in a different way from the money-lover’s, the two vicious agents will form different action-guiding impressions when faced with similar stimuli. Here I juxtapose the Stoic account of expertise, according to which experts form more precise action-guiding impressions compared to the amateur, in virtue of possessing a system of grasps (katalēpseis). So expertise enhances, whereas psychological disease degrades, the representational fidelity of the impressions that prefigure action. With these commitments, the Stoics can be seen to offer a nuanced and principled theory of cognitive penetration and to anticipate some recent proposals in epistemology and cognitive science. (shrink)

Debates about the genuine disease status of controversial diseases rely on intuitions about a range of factors. Adopting tools from experimental philosophy, this paper explores some of the factors that influence judgments about whether low sexual desire should be considered a disease and whether it should be medically treated. Drawing in part on some assumptions underpinning a divide in the literature between viewing low sexual desire as a genuine disease and seeing it as improperly medicalized, we investigate (...) whether health and disease judgments are affected by factors such as an individual’s gender, the cause of the low desire, whether the desire is high or low, and both personal and societal valuations of the condition. Our main findings indicate that (a) the cause of a condition influences whether it is judged a disorder, (b) how the individual values the condition influences whether the condition is seen as a proper target of medical intervention, and (c) perceived dysfunction influences judgments regarding health, disorder classification, medicalization, and medical intervention. Our findings help further illuminate the intricate interplay of factors that influence judgments about health and disease in controversial conditions. (shrink)

In the contemporary biomedical literature, every disease is considered genetic. This extension of the concept of genetic disease is usually interpreted either in a trivial or genocentrist sense, but it is never taken seriously as the expression of a genetic theory of disease. However, a group of French researchers defend the idea of a genetic theory of infectious diseases. By identifying four common genetic mechanisms (Mendelian predisposition to multiple infections, Mendelian predisposition to one infection, and major gene (...) and polygenic predispositions), they attempt to unify infectious diseases from a genetic point of view. In this article, I analyze this explicit example of a genetic theory, which relies on mechanisms and is applied only to a specific category of diseases, what we call “a regional genetic theory.” I have three aims: to prove that a genetic theory of disease can be devoid of genocentrism, to consider the possibility of a genetic theory applied to every disease, and to introduce two hypotheses about the form that such a genetic theory could take by distinguishing between a genetic theory of diseases and a genetic theory of Disease. Finally, I suggest that network medicine could be an interesting framework for a genetic theory of Disease. (shrink)

Cardiovascular diseases, including heart disease, pose a significant global health challenge, contributing to a substantial burden on healthcare systems and individuals. Early detection and accurate prediction of heart disease are crucial for timely intervention and improved patient outcomes. This research explores the potential of neural networks in predicting heart disease using a dataset collected from Kaggle, consisting of 1025 samples with 14 distinct features. The study's primary objective is to develop an effective neural network model for binary (...) classification, identifying the presence or absence of heart disease. The neural network architecture includes an input layer, a hidden layer, and an output layer, designed to capture intricate relationships within the dataset. Rigorous training and validation processes, accompanied by data preprocessing steps, ensure the model's robustness and generalization capabilities. The results demonstrate promising performance, with an accuracy of 92% and an average error of 0.062. Moreover, an analysis of feature importance highlights key predictors, including "oldpeak," "thalach," "trestbps," "ca," "thal," "cp," "chol," "sex," "restecg," "age," "slope," "fbs," and "exang." This research contributes to the field of predictive healthcare by leveraging neural networks to enhance heart disease prediction. The developed model offers the potential for early identification of individuals at risk, facilitating timely medical interventions and ultimately improving public health. Further exploration of machine learning techniques in healthcare promises to reshape disease prediction and prevention strategies. (shrink)

The Infectious Disease Ontology (IDO) is a suite of interoperable ontology modules that aims to provide coverage of all aspects of the infectious disease domain, including biomedical research, clinical care, and public health. IDO Core is designed to be a disease and pathogen neutral ontology, covering just those types of entities and relations that are relevant to infectious diseases generally. IDO Core is then extended by a collection of ontology modules focusing on specific diseases and pathogens. In (...) this paper we present applications of IDO Core within various areas of infectious disease research, together with an overview of all IDO extension ontologies and the methodology on the basis of which they are built. We also survey recent developments involving IDO, including the creation of IDO Virus; the Coronaviruses Infectious Disease Ontology (CIDO); and an extension of CIDO focused on COVID-19 (IDO-CovID-19).We also discuss how these ontologies might assist in information-driven efforts to deal with the ongoing COVID-19 pandemic, to accelerate data discovery in the early stages of future pandemics, and to promote reproducibility of infectious disease research. (shrink)

Identifying the necessary and sufficient conditions for individuating and classifying diseases is a matter of great importance in the fields of law, ethics, epidemiology, and of course, medicine. In this paper, I first propose a means of achieving this goal, ensuring that no two distinct disease-types could correctly be ascribed to the same disease-token. I then posit a metaphysical ontology of diseases—that is, I give an account of what a disease is. This is essential to providing the (...) most effective means of interfering with disease processes. Following existing work in the philosophy of medicine and epidemiology (primarily Christopher Boorse; Caroline Whitbeck; Alexander Broadbent), philosophy of biology (Joseph LaPorte; D.L. Hull), conditional analyses of causation (J.L. Mackie; David Lewis), and recent literature on dispositional essentialism (Stephen Mumford and Rani Anjum; Alexander Bird), I endorse a dispositional conception of disease. Following discussion of various conceptions of disease-identity, their relations to the clinical and pathological effects of the diseases in question, and how diseases are treated, I conclude (i) that diseases should be individuated by their causes, and (ii) that diseases are causal processes best seen as simultaneously acting sequences of mutually manifesting dispositions. (shrink)

Our goal in this paper is to articulate a precise concept of at least a certain kind of disease-mongering, showing how pharmaceutical marketing can commercially exploit certain diseases when their best definition is given through the success of a treatment in a clinical trial. We distinguish two types of disease-mongering according to the way they exploit the definition of the trial population for marketing purposes. We argue that behind these two forms of disease-mongering there are two well-known (...) problems in the statistical methodology of clinical trials (the reference class problem and the distinction between statistical and clinical significance). Overcoming them is far from simple. (shrink)

Response to commentary. We are grateful to Crockett and Craigie for their interesting remarks on our paper. We accept Crockett’s claim that there is a need for caution in drawing inferences about patient groups from work on healthy volunteers in the laboratory. However, we believe that the evidence we cited established a strong presumption that many of the patients who are routinely taking a medication, including many people properly prescribed the medication for a medical condition, have morally significant aspects of (...) their cognition and behavior modified in a way that is unintended and may sometimes be unwelcome. Crockett notes that in some cases the effects of long-term drug use may differ, sometimes markedly, from the effects of short-term use. However, if acute use of a drug affects a neural system involved in mediating moral cognition or behavior, this nevertheless provides some evidence that chronic use of the drug may affect that same system and thus have morally significant effects. It is also plausible, in some cases, that an acute moral effect would give rise to a chronic moral effect via cognitive mechanisms. ... (shrink)

This is a collection of essays from contemporary philosophers, artists, and writers on the intersection of speculative philosophy and speculative horror fiction. The book contains fourteen essays and an introduction. I edited the book and wrote the introduction. Topics considered include human extinction; anonymity, otherness, and alienation; whether horror is a genre; and the relationship between speculation and Kant’s critical philosophy.

Parkinson's Disease (PD) is a long-term degenerative disorder of the central nervous system that mainly affects the motor system. The symptoms generally come on slowly over time. Early in the disease, the most obvious are shaking, rigidity, slowness of movement, and difficulty with walking. Doctors do not know what causes it and finds difficulty in early diagnosing the presence of Parkinson’s disease. An artificial neural network system with back propagation algorithm is presented in this paper for helping (...) doctors in identifying PD. Previous research with regards to predict the presence of the PD has shown accuracy rates up to 93% [1]; however, accuracy of prediction for small classes is reduced. The proposed design of the neural network system causes a significant increase of robustness. It is also has shown that networks recognition rates reached 100%. (shrink)

Whipple disease is a rare, infectious, disease first described from a single case by Whipple in 1907. As well as characterising the clinical and pathological features of the condition, Whipple made two suggestions regarding its aetiology. These were either than the disease was caused by an infectious agent, or that it was of metabolic origin. As the disease is now thought to be caused by infection with the bacterium Tropheryma whipplei, historical reviews of the history of (...) the disease typically mention only the first of these suggestions. In this paper, we therefore revisit Whipple’s other theory. We argue that a diverse and often successful research programme was developed around this mechanism of disease causation which gave rise to many useful findings on the condition. In the later parts of this article, we then turn to discuss the surprising neglect of this period of Whipple disease research in the current literature, and conclude by offering a brief reconstruction of this early history suitable for use in a technical context. (shrink)

Artificial Intelligence (AI) technologies are now widely used in a variety of fields to aid with knowledge acquisition and decision-making. Health information systems, in particular, can gain the most from AI advantages. Recently, symptoms-based illness prediction research and manufacturing have grown in popularity in the healthcare business. Several scholars and organisations have expressed an interest in applying contemporary computational tools to analyse and create novel approaches for rapidly and accurately predicting illnesses. In this study, we present a paradigm for assessing (...) the efficacy of combining Machine Learning (ML) and Natural Language Processing (NLP) technologies in a disease prediction system. We scraped a disease-symptom dataset with NLP characteristics from one of the UK's most trusted National Health Service (NHS) websites as an example. In addition, we will thoroughly examine our data using symptom frequency, similarity, and clustering analysis. As a consequence, we can observe that the forecast has a high efficiency rate, but there are still some challenges to work out. (shrink)

Deutsche Krankheit: eine Diagnosestellung mit Rückblick und Ausblick auf Krankheitsverlauf.

In this article I seek to say what it is for something to count as a neglected disease. I argue that neglect should be defined in terms of efforts at prevention, mitigation and cure, and not solely in terms of research dollars per disability-adjusted life-year. I further argue that the trend towards multifactorialism and risk factor thinking in modern epidemiology has lent credibility to the erroneous view that the primary problem with neglected diseases is a lack of research. A (...) more restrictive contrastive model of disease is endorsed as better suited to the definition of neglected disease. (shrink)

Some ‘naturalist’ accounts of disease employ a biostatistical account of dysfunction, whilst others use a ‘selected effect’ account. Several recent authors have argued that the biostatistical account offers the best hope for a naturalist account of disease. We show that the selected effect account survives the criticisms levelled by these authors relatively unscathed, and has significant advantages over the BST. Moreover, unlike the BST, it has a strong theoretical rationale and can provide substantive reasons to decide difficult cases. (...) This is illustrated by showing how life-history theory clarifies the status of so-called diseases of old age. The selected effect account of function deserves a more prominent place in the philosophy of medicine than it currently occupies. _1_ Introduction _2_ Biostatistical and Selected Effect Accounts of Function _3_ Objections to the Selected Effect Account _3.1_ Boorse _3.2_ Kingma _3.3_ Hausman _3.4_ Murphy and Woolfolk _4_ Problems for the Biostatistical Account _4.1_ Schwartz _5_ Analysis versus Explication _6_ Explicating Dysfunction: Life History Theory and Senescence _7_ Conclusion. (shrink)

Brain-related diseases are among the most difficult diseases due to their sensitivity, the difficulty of performing operations, and their high costs. In contrast, the operation is not necessary to succeed, as the results of the operation may be unsuccessful. One of the most common diseases that affect the brain is Alzheimer’s disease, which affects adults, a disease that leads to memory loss and forgetting information in varying degrees. According to the condition of each patient. For these reasons, it (...) is important to classify memory loss and to know the patient at what level and his assessment of Alzheimer's disease through CT scans of the brain. In this thesis, we review ways and techniques to use deep learning classification to classifying the Alzheimer's Disease The proposed method used to improve patient care, reduce costs, and allow fast and reliable analysis in large studies. The model will be designed using Python language for implementing the system, which is very useful for doctors, classifying the Alzheimer's Disease, was used. The model used 70% from image for training and 30% from image for validation, our trained model achieved an accuracy of 100% on a held-out test set. (shrink)

Vaccination complacency occurs when perceived risks of vaccine-preventable diseases are sufficiently low so that vaccination is no longer perceived as a necessary precaution. Disease outbreaks can once again increase perceptions of risk, thereby decrease vaccine complacency, and in turn decrease vaccine hesitancy. It is not well understood, however, how change in perceived risk translates into change in vaccine hesitancy. -/- We advance the concept of vaccine propensity, which relates a change in willingness to vaccinate with a change in perceived (...) risk of infection—holding fixed other considerations such as vaccine confidence and convenience. (shrink)

There is no doubt that custard apple diseases are among the important reasons that destroy the Custard Apple plant and its agricultural crops. This leads to obvious damage to these plants and they become inedible. Discovering these diseases is a good step to provide the appropriate and correct treatment. Determining the treatment with high accuracy depends on the method used to correctly diagnose the disease, expert systems can greatly help in avoiding damage to these plants. The expert system correctly (...) diagnoses Custard Apple disease to make it easier for farmers to find the right treatment based on the appropriate diagnosis. Objectives: A specialized syllable language system was established for the diagnosis of Custard Apple plant disease. (shrink)

Similarly to other accounts of disease, Christopher Boorse’s Biostatistical Theory (BST) is generally presented and considered as conceptual analysis, that is, as making claims about the meaning of currently used concepts. But conceptual analysis has been convincingly critiqued as relying on problematic assumptions about the existence, meaning, and use of concepts. Because of these problems, accounts of disease and health should be evaluated not as claims about current meaning, I argue, but instead as proposals about how to define (...) and use these terms in the future, a methodology suggested by Quine and Carnap. I begin this article by describing problems with conceptual analysis and advantages of “philosophical explication,” my favored approach. I then describe two attacks on the BST that also question the entire project of defining “disease.” Finally, I defend the BST as a philosophical explication by showing how it could define useful terms for medical science and ethics. (shrink)

Mental and behavioral disorders represent a significant portion of the public health burden in all countries. The human cost of these disorders is immense, yet treatment options for sufferers are currently limited, with many patients failing to respond sufficiently to available interventions and drugs. High quality ontologies facilitate data aggregation and comparison across different disciplines, and may therefore speed up the translation of primary research into novel therapeutics. Realism-based ontologies describe entities in reality and the relationships between them in such (...) a way that – once formulated in a suitable formal language – the ontologies can be used for sophisticated automated reasoning applications. Reference ontologies can be applied across different contexts in which different, and often mutually incompatible, domain-specific vocabularies have traditionally been used. In this contribution we describe the Mental Functioning Ontology (MF) and Mental Disease Ontology (MD), two realism-based ontologies currently under development for the description of humanmental functioning and disease. We describe the structure and upper levels of the ontologies and preliminary application scenarios, and identify some open questions. (shrink)

This paper aims is to present the design and development of an intelligent tutoring system for teaching students about stomach diseases to help and give them a clear idea about stomach ulcer diseases. Furthermore, the researchers designed an intelligent tutoring system with a clear interface including 3D animation with Delphi that show how the ulcer appears in the stomach with more details about the disease, after that there are some questions researchers going to adopt from clinical books about the (...) diseases that show the students how to diagnose the diseases. This system integrated Delphi programming with multimedia elements such as (voice, motion, text, photo, and interactive) to carry out the project. The idea of this paper is considering the intelligent tutoring system for students who are studying medicine to enhance their knowledge and deep understanding about the diseases. (shrink)