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)

Venomous snakebite is a neglected tropical disease and disease of poverty, affecting hundreds of thousands of people annually. The only effective medical intervention for snakebite is antivenom, produced primarily using captive venomous snakes as a source of venom. This paper analyzes snakes’ welfare at venom labs within this global health context. I recommend significant changes to improve the welfare of captive snakes, particularly in light of recent ethological research and attention on snakes. These recommendations are broadly consequentialist, aiming to (...) improve the lives of the snakes and ensure that people have increased access to affordable antivenom. (shrink)

Many countries in Africa, and more generally those in the Global South with tropical areas, are plagued by illnesses that the wealthier parts of the world (mainly ‘the West’) neither suffer from nor put systematic effort into preventing, treating or curing. What does an ethic with a recognizably African pedigree entail for the ways various agents ought to respond to such diseases? As many readers will know, a characteristically African ethic prescribes weighty duties to aid on the part of (...) those in a position to do so, and it therefore entails that there should have been much more contribution from the Western, ‘developed’ world. However, what else does it prescribe, say, on the part of sub-Saharan governments and the African Union, and are they in fact doing it? I particularly seek to answer these questions here, by using the 2013-16 Ebola crisis in West Africa to illustrate what should have happened but what by and large did not. (shrink)

This paper aims to recover the history of health concept evolution from its birth in Ancient Greece to the contemporary days, drawing an overview of the firsts philosophical thoughts about health in distinctive historical periods, analyzing how this concept has been impacted by knowledge improvement and both research and technological discoveries over time. In order to understand the persistence of Neglected Tropical Diseases which causes physical disabilities and social discrimination, this paper will focus on Leprosy and Cutaneous Leishmaniasis (...) and its relation to social inequality mainly in developing countries. These approaches on the understanding of the health-disease binomial are necessary to reflect on health in the course of human history and, from there, to promote joint actions both in the area of scientific research and health education. (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)

In a recent article, Marilyn Baffoe-Bonnie offers three arguments for conducting CRISPR/Cas9 biotechnology research to cure sickle-cell disease (SCD) based on addressing historical and current injustices in SCD research and care. I show that her second and third arguments suffer from roughly the same defect, which is that they really argue for something else rather than for conducting CRISPR/Cas9 research in particular. For instance, the second argument argues that conducting this gene therapy research would improve the relationship between SCD sufferers (...) (who are mostly of African descent) and health care providers. But really what is essential in improving this relationship is for those providers to genuinely care and be concerned, and this could be lacking even with the CRISPR research being done. Indeed, this relationship could be improved even without that research being done, as long as there is genuine concern. Thus, this argument actually argues for the need for genuine concern. As for the third argument, one (of two) problems arises because it claims that CRISPR research for SCD should be pursued because the benefits would be shared by even non-research-participants, as non-participants would be encouraged. However, this argues for any research for SCD, not for CRISPR research in particular. I conclude that a better justice-based argument will use only Baffoe-Bonnie’s first argument, which is based on historic neglect of an actual cure for SCD (going beyond merely management or transplant therapies). (shrink)

Taking into consideration the extremely harsh public health conditions faced by the majority of the world population, the Health Impact Fund (HIF) proposal seeks to make the intellectual property regimes more in line with human rights obligations. While prioritizing access to medicines and research on neglected diseases, the HIF makes many compromises in order to be conceived as politically feasible and to retain a compensation character that makes its implementation justified solely on basis of negative duties. Despite that (...) current global health realities make such steps reasonable, the paper looks up the negative effects on one overlooked human right: the right to participate in scientific advancement. (shrink)

Precision medicine and molecular systems medicine (MSM) are highly utilized and successful approaches to improve understanding, diagnosis, and treatment of many diseases from bench-to-bedside. Especially in the COVID-19 pandemic, molecular techniques and biotechnological innovation have proven to be of utmost importance for rapid developments in disease diagnostics and treatment, including DNA and RNA sequencing technology, treatment with drugs and natural products and vaccine development. The COVID-19 crisis, however, has also demonstrated the need for systemic thinking and transdisciplinarity and the (...) limits of MSM: the neglect of the bio-psycho-social systemic nature of humans and their context as the object of individual therapeutic and population-oriented interventions. COVID-19 illustrates how a medical problem requires a transdisciplinary approach in epidemiology, pathology, internal medicine, public health, environmental medicine, and socio-economic modeling. Regarding the need for conceptual integration of these different kinds of knowledge we suggest the application of general system theory (GST). This approach endorses an organism-centered view on health and disease, which according to Ludwig von Bertalanffy who was the founder of GST, we call Organismal Systems Medicine (OSM). We argue that systems science offers wider applications in the field of pathology and can contribute to an integrative systems medicine by (i) integration of evidence across functional and structural differentially scaled subsystems, (ii) conceptualization of complex multilevel systems, and (iii) suggesting mechanisms and non-linear relationships underlying the observed phenomena. We underline these points with a proposal on multi-level systems pathology including neurophysiology, endocrinology, immune system, genetics, and general metabolism. An integration of these areas is necessary to understand excess mortality rates and polypharmacological treatments. In the pandemic era this multi-level systems pathology is most important to assess potential vaccines, their effectiveness, short-, and long-time adverse effects. We further argue that these conceptual frameworks are not only valid in the COVID-19 era but also important to be integrated in a medicinal curriculum. (shrink)

Climate change, pollution, and deforestation have a negative impact on global mental health. There is an environmental justice dimension to this challenge as wealthy people and high-income countries are major contributors to climate change and pollution, while poor people and low-income countries are heavily affected by the consequences. Using state-of-the art data mining, we analyzed and visualized the global research landscape on mental health, climate change, pollution and deforestation over a 15-year period. Metadata of papers were exported from PubMed®, and (...) both relevance and relatedness of terms in different time frames were computed using VOSviewer. Co-occurrence graphs were used to visualize results. The development of exemplary terms over time was plotted separately. The number of research papers on mental health and environmental challenges is growing in a linear fashion. Major topics are climate change, chemical pollution, including psychiatric medication in wastewater, and neurobiological effects. Research on specific psychiatric syndromes and diseases, particularly on their ethical and social aspects is less prominent. There is a growing body of research literature on links between mental health, climate change, pollution, and deforestation. This research provides a graphic overview to mental healthcare professionals and political stakeholders. Social and ethical aspects of the climate change-mental health link have been neglected, and more research is needed. (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)

A dissociated area of medical research warrants bioethical consideration: a proposed transplantation of a donor’s entire body, except head, to a patient with a fatal degenerative disease. The seeming improbability of such an operation can only underscore the need for thorough bioethical assessment: Not assessing a case of such potential ethical import, by showing neglect instead of facing the issue, can only compound the ethical predicament, perhaps eroding public trust in ethical medicine. This article discusses the historical background of full-body (...) transplantation, documents the seriousness of its current pursuit, and builds an argument for why prima facie this type of transplant is bioethically distinct. Certainly, this examination can only be preliminary, indicating what should be a wide and vigorous discussion among practitioners and ethicists. It concludes with practical suggestions for how the medical and bioethics community may proceed with ethical assessment. (shrink)

Reification is to abstraction as disease is to health. Whereas abstraction is singling out, symbolizing, and systematizing, reification is neglecting abstractive context, especially functional, historical, and analytical-level context. William James and John Dewey provide similar and nuanced arguments regarding the perils and promises of abstraction. They share an abstraction-reification account. The stages of abstraction and the concepts of “vicious abstractionism,” “/the/ psychologist’s fallacy,” and “the philosophic fallacy” in the works of these pragmatists are here analyzed in detail. For instance, in (...) 1896 Dewey exposes various fallacies associated with reifying dualistic reflex arc theory. The conclusion prescribes treatments (pluralism and assumption archaeology) for de-reifying ill models (i.e., universalized, narrowed, and ontologized models) in contemporary scientific fields such as cognitive science and biology. (shrink)

In recent years, philosophers have identified a number of moral and psychological harms associated with the attention economy (Alysworth & Castro, 2021; Castro & Pham, 2020; Williams, 2018). Missing from many of these accounts of the attention economy, however, is what exactly attention is. As a result of this neglect of the cognitive science of attention, many of these accounts are not empirically credible. They rely on oversimplified and unsophisticated accounts of not only attention, but self- control, and addiction as (...) well. Of note are accounts of the attention economy that rely on the ‘brain disease’ rhetoric of addiction and subsequent control failures (Aylsworth & Castro, 2021; Bhargava & Velasquez, 2021), accounts that rely on a strict dichotomy of top-down vs. bottom-up attention (Williams, 2018; Aylsworth & Castro, 2021), and accounts that construe attention as a limited resource (Williams, 2018). -/- Drawing on recent work from the neuroscience and psychology of attention, I demonstrate the shortcomings of these accounts and sketch a way forward for an empirically grounded account of the attention economy. These accounts tend to uphold strict dichotomies of voluntary control (e.g., compulsion versus choice, dual-process models of self-control, and top-down versus bottom-up) that cannot account for the complexities of attentional control, mental agency, and decision-making. As such, these empirically and conceptually impoverished accounts cannot adequately address the current so-called crisis of attention. To better understand the harms associated with the attention economy, we need an empirically responsible account of the nature and function of attention and mental agency. (shrink)

The aim of this paper is to develop and defend an Attentional View of bodily awareness, on which attention is necessary for bodily awareness. The original formulation of the Attentional View is due to Marcel Kinsbourne. First, I will show that the Attentional View of bodily awareness as formulated by Kinsbourne is superior to other accounts in the literature for characterizing the relationship between attention and bodily awareness. Kinsbourne’s account is the only account in the literature so far which can (...) accommodate key neurological diseases such as personal neglect. Second, when I consider Kinsbourne’s view in more detail, I will argue that Kinsbourne’s Attentional View faces problems because it is too reductive. Kinsbourne deviates from the standard taxonomy on which there is a body schema and a body image. Instead he reduces the body image to the neural representation of the body in the somatosensory cortex, the body schema and attentional shifts. I will present two challenges to Kinsbourne’s view which demonstrate that Kinsbourne’s reduction of the body image is unsuccessful. Finally, I will present a revised version of the Attentional View that is both empirically adequate and philosophically satisfactory. (shrink)

Recent studies demonstrating epigenetic and developmental sensitivity to early environments, as exemplified by fields like the Developmental Origins of Health and Disease (DOHaD) and environmental epigenetics, are bringing new data and models to bear on debates about race, genetics, and society. Here, we first survey the historical prominence of models of environmental determinism in early formulations of racial thinking to illustrate how notions of direct environmental effects on bodies have been used to naturalize racial hierarchy and inequalities in the past. (...) Next, we conduct a scoping review of postgenomic work in environmental epigenetics and DOHaD that looks at the role of race/ethnicity in human health (2000–2021). Although there is substantial heterogeneity in how race is conceptualized and interpreted across studies, we observe practices that may unwittingly encourage typological thinking, including: using DNA methylation as a novel marker of racial classification; neglect of variation and reversibility within supposedly homogenous racial groups; and a tendency to label and reify whole groups as pathologized or impaired. Even in the very different politico-economic and epistemic context of contemporary postgenomic science, these trends echo deeply held beliefs in Western thinking which claimed that different environments shape different bodies and then used this logic to argue for essential differences between Europeans and non-Europeans. We conclude with a series of suggestions on interpreting and reporting findings in these fields that we feel will help researchers harness this work to benefit disadvantaged groups while avoiding the inadvertent dissemination of new and old forms of stigma or prejudice. (shrink)

This essay attempts to explain the traditional and contemporary philosophical neglect of disability by arguing that the philosophical prioritization of rationality leads to a distinctly philosophical conception of disability as a negative category of non-normative embodiment. I argue that the privilege given to rationality as distinctive of what it means to be both a human subject and a moral agent informs supposedly rational norms of human embodiment. Non-normative types of embodiment in turn can only be understood in contradistinction to these (...) rationalized norms, which are predicated on the elimination of certain features and types of embodiment deemed inimical to reason. To establish this thesis, I focus on Platonic philosophy and the Republic as Platonic conceptions of reason and normative types of embodiment have a historical and conceptual influence on contemporary assumptions concerning rational human nature, medicine, mental health, vice, disease, and impairment. (shrink)

Genetically engineered (GE) insects, such as the GE OX513A Aedes aegypti mosquitoes, have been designed to suppress their wild-type populations so as to reduce the transmission of vector-borne diseases in humans. Apart from the ecological and epidemiological uncertainties associated with this approach, such biotechnological approaches may be used by individual governments or the global community of nations to avoid addressing the underlying structural, systemic causes of those infections... We discuss here key ethical questions raised by the use of GE (...) mosquitoes, with the aim of fostering discussion between the public, researchers, policy makers, healthcare organizations, and regulatory agencies at the local, national, and international levels. We affect that goal by outlining a procedural approach to decision-making about the use of the “biotechnology” that goes beyond “community engagement.” The protocol we advocate for entails informed deliberations and decision-making at the community level. It is designed to ensure that the voices of the marginalized and vulnerable groups that would be disproportionately affected by the decision are heard during the community-wide discussions. Moreover, we make the case that the values embedded in the risk assessment should be identified so that the community can make an informed decision about the use of GE insects. In addition, we advocate for the involvement of a variety of actors whose responsibility would be to ensure that the community has the opportunity to make an informed decision based on deliberations about the use of the “biotechnology.”. (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)

This review was conducted to examine the causes, diagnoses, clinical manifestations, and available treatments for Graves' disease. Keywords like "Graves' disease," "radioactive iodine," "etiology," and "treatment" were used to search for data pertaining to Textbooks on endocrinology and other papers from these sources were also located. The introduction, etiology, risk factors, symptoms, diagnosis, course of treatment, and the contribution of many factors to the beginning of Graves' disease are all covered in this review article.

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)

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)

Given the ever-present subject of consciousness wherever consciousness is, it is peculiar that consciousness researchers often mention mental states as if they are conscious independently of being the conscious states of someone [1, p. 132]. We refer to visual perceptions that become conscious, when in reality no one has ever studied mere conscious visual perceptions. What are studied are visual perceptions belonging to conscious human or animal subjects; it is the subjects who are conscious of visual stimuli, not the visual (...) perceptions. I do not know all the reasons why conscious subjects are rarely mentioned in consciousness science, but one could be pragmatic. Explaining the mysterious jump from the nonconscious nuts and bolts of neurons to the aurora borealis of consciousness is a hard problem. But it is an easy problem compared to explaining the emergence of a single conscious subject from the human brain’s 86 billion neurons [cf. 5]. Perhaps it is more practically realistic to solve the less hard problem before attempting to solve the harder hard problem. On the other hand, if we ignore a necessary condition for the presence of consciousness, our explanations of it could be plagued by inadequacy. And how can we explain our whole data set regarding consciousness if we neglect the most fundamental aspect of the data? (shrink)

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)

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)

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)

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)

In this paper, we identify some key features of what makes something a disease, and consider whether these apply to pregnancy. We argue that there are some compelling grounds for regarding pregnancy as a disease. Like a disease, pregnancy affects the health of the pregnant person, causing a range of symptoms from discomfort to death. Like a disease, pregnancy can be treated medically. Like a disease, pregnancy is caused by a pathogen, an external organism invading the host’s body. Like a (...) disease, the risk of getting pregnant can be reduced by using prophylactic measures. We address the question of whether the ‘normality’ of pregnancy, its current necessity for human survival, or the value often attached to it are reasons to reject the view that pregnancy is a disease. We point out that applying theories of disease to the case of pregnancy, can in many cases illuminate inconsistencies and problems within these theories. Finally, we show that it is difficult to find one theory of disease that captures all paradigm cases of diseases, while convincingly excluding pregnancy. We conclude that there are both normative and pragmatic reasons to consider pregnancy a disease. (shrink)

Cardiovascular diseases (CVD) represent a significant cause of morbidity and mortality worldwide, necessitating early detection for effective intervention. This research explores the application of machine learning (ML) algorithms in predicting cardiovascular diseases with enhanced accuracy by integrating optimization techniques. By leveraging data-driven approaches, ML models can analyze vast datasets, identifying patterns and risk factors that traditional methods might overlook. This study focuses on implementing various ML algorithms, such as Decision Trees, Random Forest, Support Vector Machines, and Neural Networks, (...) optimized through techniques like hyperparameter tuning, cross-validation, and feature selection to improve prediction accuracy. (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)

Given the importance of emotions in our everyday lives, it is no surprise that in recent decades the study of emotions has received tremendous attention by a number of different disciplines. Yet despite the many and great advantages that have been made in understanding the nature of emotions, there remains a class of emotional states that is understudied and that demands further elucidation. All contributions to this issue consider either emotions or aspects of emotions that deserve the label ‘neglected’. (...) In doing so, they break new theoretical ground and further our understanding of the nature of the emotions that they consider. The aim of the present paper is to introduce the special issue on neglected emotions by articulating the different ways in which emotions can be said to be neglected. (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)

One set of neglected problems consists of paradoxes of omniscience clearly recognizable as forms of the Liar, and these I have never seen raised at all. Other neglected problems are difficulties for omniscience posed by recent work on belief de se and essential indexicals. These have not yet been given the attention they deserve.

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)

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)

Intra-molecular connectivity (that is, chemical structure) does not emerge from computations based on fundamental quantum-mechanical principles. In order to compute molecular electronic energies (of C 3 H 4 hydrocarbons, for instance) quantum chemists must insert intra-molecular connectivity “by hand.” Some take this as an indication that chemistry cannot be reduced to physics: others consider it as evidence that quantum chemistry needs new logical foundations. Such discussions are generally synchronic rather than diachronic —that is, they neglect ‘historical’ aspects. However, systems of (...) interest to chemists generally are metastable . In many cases chemical systems of a given elemental composition may exist in any one of several different metastable states depending on the history of the system. Molecular structure generally depends on contingent historical circumstances of synthesis and separation, rather than solely or mainly on relative energies of alternative stable states, those energies in turn determined by relationships among components. Chemical structure is usually ‘kinetically-determined’ rather than ‘thermodynamically-determined.’ For instance, cyclical hydrocarbon ring-systems (as in cyclopropene) are produced only in special circumstances. Adequate theoretical treatments must take account of the persistent effects of such contingent historical events whenever they are relevant—as they generally are in chemistry. (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)

On 11 March 2020, the World Health Organization declared a pandemic of the COVID-19 coronavirus disease that was first recognized in China in late 2019. Among the primary effects caused by the pandemic, there was the dissemination of health preventive measures such as physical distancing, travel restrictions, self-isolation, quarantines, and facility closures. This includes the global disruption of socio-economic systems including the postponement or cancellation of various public events (e.g., sporting, cultural, or religious), supply shortages and fears of the same, (...) schools and universities closure, evacuation of foreign citizens, a rise of unemployment, changes in the international aid schemes, misinformation, and incidents of discrimination toward people affected by or suspected of having the COVID-19 disease. The pandemic has brought to the fore unpreparedness in critical areas that require attention, amid prospects and challenges. Moreover, considerable reorganization efforts are required with implications for assets, resources, norms, and value systems. COVID-19 is challenging the concept of globalization and stimulating responses at the levels of local and regional socio-economic systems that lead to the mobilization of assets that have been unrecognized earlier on, such as various forms of economic capital, social capital, cultural capital, human capital, and creative capital. For example, through digital channels, local groups are forming to create schemes of support for physical and mental wellbeing. These emerging exchanges lead to various social and technological innovations by building on skills and assets that are less important in the free-market economy, such as empathy, skills for crafts, making and fixing; locally grown microgreens; and micromanufacturing. Isolation and local living are also making it much harder to ignore the civic responsibilities towards communities, meant as individuals, vulnerable groups, and local businesses. Whilst the pandemic is limiting physical participation, this challenging time is uncovering alternative ways of mutual support, which may create long-term benefits for socio-economic systems, including environmental and biodiversity protection, reduction of the air pollution, and climate action. The pandemic’s threat to public health will hopefully be overcome with implications for disruption for an extended period that we are unable to forecast at this stage. It is key to focus on studies recognizing the activities and interventions leading to the recovery of socio-economic systems after the pandemic. Reflecting and planning on how societies and economies will go back to “business as usual” requires new forms of communication and cooperation, imaginative design thinking, new styles of management, as well as new tools and forms of participation in various public policies. Many questions related to the care of the vulnerable, economic restart, and the risk of future pandemics, to mention but a few, are already occupying the academic, scientific, experts, and activist communities, who have started to imagine the “new normal.”. (shrink)

Claims about whether or not infertility is a disease are sometimes invoked to defend or criticize the provision of state-funded treatment for infertility. In this paper, I suggest that this strategy is problematic. By exploring infertility through key approaches to disease in the philosophy of medicine, I show that there are deep theoretical disagreements regarding what subtypes of infertility qualify as diseases. Given that infertility's disease status remains unclear, one cannot uncontroversially justify or undermine its claim to medical treatment (...) by claiming that it is or is not a disease. Instead of focusing on disease status, a preferable strategy to approach the debate about state-funded treatment is to explicitly address the specific ethical considerations raised by infertility. I show how this alternative strategy can be supported by a recent theoretical framework in the philosophy of medicine, which avoids the problems associated with the concepts of health and disease. (shrink)

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)

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)

Abstract: In recent years, the outbreak of various poultry diseases has posed a significant threat to the global poultry industry. Therefore, the accurate and timely detection of chicken diseases is critical to reduce economic losses and prevent the spread of diseases. In this study, we propose a method for classifying chicken diseases using a convolutional neural network (CNN). The proposed method involves preprocessing the chicken images, building and training a CNN model, and evaluating the performance of (...) the model. The dataset used in this study comprises chicken images of three different diseases: Newcastle disease, avian influenza, and infectious bursal disease. The proposed method achieved an overall F1-score of 99.04% in classifying the chicken diseases. The results demonstrate the effectiveness of using CNN in classifying chicken diseases and provide a promising approach for early detection and diagnosis of poultry diseases. (shrink)

Introduction: The incidence of chronic low back pain (LBP) is very high in Bangladesh. There is a high prevalence of psychiatric diseases among chronic low back pain patients. But primary care physicians and specialists do not screen this association. The aims of this study were to evaluate the incidence and pattern of psychiatric diseases in chronic low back pain patients. Materials and methods: A prospective cross-sectional hospital-based study of 135 chronic low back pain patients using simple, direct, standardized (...) questionnaire including history and detailed psychiatric evaluation by a consultant psychiatrist from January to December 2014. Results: A total 69 chronic low back pain patients (51.1%) were diagnosed with psychiatric problems. Predominant group were female (65.9%), above 40 years of age (60.7%). Depression (44.9 %) and anxiety (31.9%) were the major psychiatric illness diagnosed (76.8%). Only 17.4 % patients expects complete cure. Fear of disease outcome was the commonest precipitating factor found (66.6%). With the adjuvant psychiatric management, 81.1% showed improvement clinically. Conclusion: Detecting the level of psychiatric illness among chronic low back pain patients at early stage will improve the treatment outcome. A referral system to psychiatrists by physicians needs to develop to screen the mental disorder symptoms to treat the problem. (shrink)

I aspire to answer two questions regarding the concept of a corrective duty. The first concerns what it means to wrong others, thus triggering a demand for corrections (the ground question). The second relates to the proper content of corrective duties. I first illustrate how three prominent accounts of corrective duties—the Aristotelian model of correlativity, the Kantian idea that wronging corresponds to the violation of others’ right to freedom, and the more recent continuity view—have failed to answer the two questions (...) satisfactorily. I then introduce my proposal, which holds that we wrong others when we fail to treat their status as moral agents as a source of stringent constraints on our action. I call it the moral neglect account. Once we have identified a common aim of corrective duties (counterbalancing moral neglect), we can fill their content in the various contexts in which wronging has occurred. I conclude by observing that it is not the primary role of corrective justice to assign responsibilities for damage reparations; in fact, requests for compensation make more sense if framed in distributive rather than corrective terms. (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)

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)

There are many eye diseases but the most two common retinal diseases are Age-Related Macular Degeneration (AMD), which the sharp, central vision and a leading cause of vision loss among people age 50 and older, there are two types of AMD are wet AMD and DRUSEN. Diabetic Macular Edema (DME), which is a complication of diabetes caused by fluid accumulation in the macula that can affect the fovea. If it is left untreated it may cause vision loss. Therefore, (...) early detection of diseases is a critical importance. Our main goal is to help doctors detect these diseases quickly before reaching a late stage of the disease. In ophthalmology, optical coherence tomography (OCT) is critical for evaluating retinal conditions. OCT is an imaging technique used to capture high-resolution cross-sections of the retinas of patient. In this thesis, we review ways and techniques to use deep learning classification of the optical coherence tomography images of diseases from which a Retinal is suffering. The models used to improve patient care are (VGG-16, MobileNet, ResNet-50, Inception V3, and Xception) to reduce costs and allow fast and reliable analysis in large studies. The obtained results are encouraging, since the best model ResNet-50 reaching 96.21% of testing accuracy, which is very useful for doctors, to diagnose retinal diseases. (shrink)

This paper addresses the use of dispositions in the Infectious Disease Ontology (IDO). IDO is an ontology constructed according to the principles of the Open Biomedical Ontology (OBO) Foundry and uses the Basic Formal Ontology (BFO) as an upper ontology. After providing a brief introduction to disposition types in BFO and IDO, we discuss three general techniques for representing combinations of dispositions under the headings blocking dispositions, complementary dispositions, and collective dispositions. Motivating examples for each combination of dispositions is given (...) along with a specific use case in IDO. Description logic restrictions are used to formalize statements relating to these combinations. (shrink)

Two different versions of the ending of the first additament to C. S. Peirce's 1908 article, "A Neglected Argument for the Reality of God," appear in the Collected Papers but were omitted from The Essential Peirce. In one, he linked the hypothesis of God's Reality to his entire theory of logic as semeiotic, claiming that proving the latter would also prove the former. In the other, he offered a final outline of his cosmology, in which the Reality of God (...) as Ens necessarium is indispensable to both the origin and order of our existing universe of Signs. Exploring these passages, as well as the unpublished manuscript drafts of the article, provides important insights into the key concepts of instinct and continuity within Peirce's comprehensive system of thought. (shrink)

When evolutionary explanation is transferred from its normal habitat of biology to the realm of human social, cultural, and moral concerns, a problem is often neglected. After examining arguments for and against Social Darwinism, this paper identifies this problem and proceeds by exploring the possibility of a middle-ground position according to which Social Darwinism would be enough for explaining some aspects of moral and social behaviour but not enough for explaining all aspects. The investigation indicates that this middle-ground position (...) is not viable because intentional content burdens evolutionary ethics with fundamental problems, problems that need to be resolved before any further progress is attainable. (shrink)