This research paper presents the development and evaluation of an expert system for diagnosing kidney diseases. The expert system utilizes a decision-making tree approach and is implemented using the CLIPS and Delphi frameworks. The system's accuracy in diagnosing kidney diseases and user satisfaction were evaluated. The results demonstrate the effectiveness of the expert system in providing accurate diagnoses and high user satisfaction.

Chronic kidney disease (CKD) is a global health problem with high morbidity and mortality rate, and it induces other diseases. There are no obvious incidental effects during the starting periods of CKD, patients routinely disregard to see the sickness. Early disclosure of CKD enables patients to seek helpful treatment to improve the development of this disease. AI models can effectively assist clinical with achieving this objective on account of their fast and exact affirmation execution. In this appraisal, proposed (...) a Logistic relapse framework for diagnosing CKD. Proposed calculation like NAIVE BAYES , DECISION TREE , KSTAR , LOGISITIC , AND SVM and look at these calculation and get the most noteworthy precision .AI store, which has an enormous number of missing qualities. Missing characteristics are for the most part found, taking everything into account, clinical conditions since patients might miss a couple of assessments for various reasons. By separating the misjudgements delivered by the set up models and proposed a fused model that unites determined backslide and sporadic woods by using perceptron. (shrink)

Every year, hundreds of patients in England die whilst waiting for a kidney transplant, and this is evidence that the current system of altruistic-based donation is not sufficient to address the shortage of kidneys available for transplant. To address this problem, we propose a monopsony system whereby kidney donors can opt-in to receive financial compensation, whilst still preserving the right of individuals to donate without receiving any compensation. A monopsony system describes a market structure where there is only (...) one ‘buyer’—in this case the National Health Service. By doing so, several hundred lives could be saved each year in England, wait times for a kidney transplant could be significantly reduced, and it would lessen the burden on dialysis services. Furthermore, compensation would help alleviate the common disincentives to living kidney donation, such as its potential associated health and psychological costs, and it would also help to increase awareness of living kidney donation. The proposed system would also result in significant cost savings that could then be redirected towards preventing kidney disease and reducing health disparities. While concerns about exploitation, coercion, and the ‘crowding out’ of altruistic donors exist, we believe that careful implementation can mitigate these issues. Therefore, we recommend piloting financial compensation for living kidney donors at a transplant centre in England. (shrink)

Background: Arthritis is very common but is not well understood. Actually, “arthritis” is not a single disease; it is an informal way of referring to joint pain or joint disease. There are more than 100 different types of arthritis and related conditions. People of all ages, sexes and races can and do have arthritis, and it is the leading cause of disability in America. More than 50 million adults and 300,000 children have some type of arthritis. It is most common (...) among women and occurs more frequently as people get older. Common arthritis joint symptoms include swelling, pain, stiffness and decreased range of motion. Symptoms may come and go. They can be mild, moderate or severe. They may stay about the same for years, but may progress or get worse over time. Severe arthritis can result in chronic pain, inability to do daily activities and make it difficult to walk or climb stairs. Arthritis can cause permanent joint changes. These changes may be visible, such as knobby finger joints, but often the damage can only be seen on X-ray. Some types of arthritis also affect the heart, eyes, lungs, kidneys and skin as well as the joints. Objectives: The main goal of this expert system is to get the appropriate diagnosis of disease and the correct treatment and give the appropriate method of treatment through several tips that concern the disease and how to treat it and we will see it through the application on the expert system. Methods: in this paper the design of the proposed Expert System which was produced to help Orthopedist in diagnosing Arthritis disease through its symptoms such as: pain on pressure in a joint , Inflammation indicated by joint swelling, Stiffness especially in the morning , Loss of flexibility of joint, Limited, joint movement, Deformity of the joints , Weight loss and fatigue , Non-specific fever and Crepitus. The proposed expert system presents an overview about Arthritis disease is given, the cause of diseases is outlined and the treatment of disease whenever possible is given out. SL5 Object Expert System language was used for designing and implementing the proposed expert system. Results: The proposed Arthritis disease diagnosis expert system was evaluated by Orthopedics students and they were satisfied with its performance. Conclusions: The Proposed expert system is very useful for Orthopedist, patients with arthritis and newly graduated Orthopedics students. (shrink)

Metformin is considered the first-line treatment as a monotherapy for patients with type 2 diabetes mellitus. Emerging evidence suggests that metformin may have a renoprotective role; therefore, understanding the impact of metformin dose and therapy duration on renal function may significantly improve renal outcomes in type 2 diabetes patients. This study aims to investigate the renoprotective effects of metformin by analyzing its dose-dependent impacts on the estimated glomerular filtration rate in patients with type 2 diabetes mellitus. A retrospective cross-sectional study (...) design was used from September 2022 to October 2023. Data from 302 type 2 diabetes patients were collected from patient files at the Benghazi Diabetic Center and the Aljabal Al-Alkdar Diabetic Center, including all with type 2 diabetes mellitus patients on varying doses of metformin. The collected data included age, gender, metformin dose, duration of metformin therapy, urea, and creatinine. Exclusion criteria included patients with significant comorbidities such as chronic kidney disease (other than diabetic nephropathy), liver disease, heart failure, or malignancy; those taking nephrotoxic medications; individuals with recent acute illnesses or surgical procedures; pregnant or lactating women; participants with inadequate medical records; and patients who were non-adherent to metformin therapy. Survival analysis was conducted to evaluate the effect of different metformin doses on the estimated glomerular filtration rate. The study analyzed 302 diabetic patients, of whom 46.0% were male and 54.0% were female. The age was 58.3±11.9 years. The HbA1c was 7.7%±1.3%. The duration of diabetes was 11.4±8.1 years. The creatinine was 1.0±0.9 mg/dL, and the urea was 36.7±23.8 mg/dL. Data analysis revealed a statistically significant difference in survival distribution across the dose groups. Different metformin doses significantly impact the estimated glomerular filtration rate, suggesting that dosage plays a crucial role in maintaining renal function. (shrink)

Uric acid has increasingly been associated with insulin resistance, hyperinsulinemia, and type 2 diabetes mellitus. Diabetic patients who are hyperuricemic have a risk of developing diabetic complications. Pathogenesis of uric acid may decrease nitric oxide bioavailability in vascular smooth muscle, endothelial cells and direct scavenging of nitric oxide by uric acid. A decrease in endothelial nitric oxide production by uric acid has also been associated with endothelial dysfunction and insulin resistance. This study aims to determine the relationship between uric acid (...) and glucose levels in patients with type 2 diabetes mellitus. The study included 161 Libyan patients (67 males and 94 females) diagnosed with type 2 diabetes mellitus. Both levels of serum uric acid and hemoglobin A1c (HbA1c) were determined. The patients were divided into two groups. The controllable diabetic group with HbA1c of less than 06.0% and the uncontrollable diabetic group with HbA1c of more than 06.0%. Patients who are suffering from type 2 diabetes mellitus without complications were included whereas patients with smoking, alcoholism, nephrotic disease, malignancy, hepatitis, and renal failure or kidney disease were excluded. The mean and standard deviation of uric acid, HbA1c and Pearson correlation coefficient test were considered. In the controllable diabetic group, serum uric acid mean was found to be 4.807±1.39 and HbA1c was found to be 5.032±1.39. In the uncontrollable diabetic group, serum uric acid was 4.897±1.66 and HbA1c was 8.396±1.65. Uric acid level has significantly been correlated with HBA1C in controlled and uncontrolled diabetic patients (p<0.05). In addition, the uric acid level was found to be higher in the uncontrolled diabetic group than that in the controlled group (p<0.05). A possible relationship between serum uric acid and the incidence of type 2 diabetes mellitus was noted. Thus, uric acid can be used as a potential biomarker to indicate impaired glucose metabolism. (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 2013 Rostock Symposium on Systems Biology and Bioinformatics in Aging Research was again dedicated to dissecting the aging process using in silico means. A particular focus was on ontologies, as these are a key technology to systematically integrate heterogeneous information about the aging process. Related topics were databases and data integration. Other talks tackled modeling issues and applications, the latter including talks focussed on marker development and cellular stress as well as on diseases, in particular on diseases (...) of kidney and skin. (shrink)

A precise overview of pediatric emergencies would require taxological considerations around the differences between strictly neurological factors, as modulated both via neuroanatomical differentiation in the context of normal vs. abnormal biological development, and underlying neurofunctional mechanisms, and the connection with such processes with the neuromodulated activation of digestive processes. Furthermore, an important distinction between nephrological considerations and urological considerations is necessary, more specifically, by focusing on the treatment of diseases affecting the kidneys and their ability to function in the (...) first case, and on the treatment of diseases affecting the urinary tract in the latter. In this paper, we will present a general overview of the most important aspects of each category, starting with the brief description of neurological emergencies as indicating a general (system-based vs. localized) deterioration of mental capacity, with added possible partial or full loss of cognitive capacities and/or impaired perceptual modalities and consciousness, with or without response to stimuli. (shrink)

Kidney stones pose a significant health concern, and early detection can lead to timely intervention and improved patient outcomes. This research endeavours to predict the presence of kidney stones based on urine analysis, utilizing a neural network model. A dataset of 552 urine specimens, comprising six essential physical characteristics (specific gravity, pH, osmolarity, conductivity, urea concentration, and calcium concentration), was collected and prepared. Our proposed neural network architecture, featuring three layers (input, hidden, output), was trained and validated, achieving (...) an impressive accuracy of 98.67% and an average error of 0.012. In addition to model performance, feature importance analysis was conducted to determine the most influential factors in predicting kidney stone presence. The findings underscore the significance of urea concentration, specific gravity, calcium concentration, conductivity, osmolarity, and pH as key indicators. This research contributes to the early diagnosis of kidney stones and demonstrates the potential of neural networks in medical diagnostics. The clinical implications of these findings are discussed, emphasizing the importance of timely intervention in managing kidney stone-related health issues. (shrink)

Janet Radcliffe Richards’ The Ethics of Transplants outlines a novel framework for moral inquiry in practical contexts and applies it to the topic of paid living kidney donation. In doing so, Radcliffe Richards makes two key claims: that opponents of organ markets bear the burden of proof, and that this burden has not yet been satisfied. This paper raises four related objections to Radcliffe Richards’ methodological framework, focusing largely on how Radcliffe Richards uses this framework in her discussion of (...) kidney sales. We conclude that Radcliffe Richards’ method of inquiry hinders our ability to answer the very question that it ought to help us resolve: What is there best reason to do, all things considered? (shrink)

There is a global shortage of organs for transplantation and despite many governments making significant changes to their organ donation systems, there are not enough kidneys available to meet the demand. This has led scientists and clinicians to explore alternative means of meeting this organ shortfall. One of the alternatives to human organ transplantation is xenotransplantation, which is the transplantation of organs, tissues, or cells between different species. The resurgence of interest in xenotransplantation and recent scientific breakthroughs suggest that genetically-engineered (...) pigs may soon present a realistic alternative as sources of kidneys for clinical transplantation. It is therefore important for nurses and allied health professionals to understand what is involved in xenotransplantation and its future implications for their clinical practices. First, we explore the insufficiency of different organ donation systems to meet the kidney shortage. Second, we provide a background and a summary of the progress made so far in xenotransplantation research. Third, we discuss some of the scientific, technological, ethical, and economic issues associated with xenotransplantation. Finally, we summarise the literature on the attitudes of healthcare professionals toward xenotransplantation. (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)

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 Canada, there are currently no guidelines at either the federal or provincial level regarding the provision of kidney transplantation services to foreign nationals (FN). Renal transplant centres have, in the past, agreed to put refugee claimants and other FNs on the renal transplant waiting list, in part, because these patients (refugee claimants) had health insurance through the Interim Federal Health Programme to cover the costs of medication and hospital care. However, severe cuts recently made to this programme have (...) forced clinicians to question whether they should continue with transplants for FNs, for financial and ethical reasons. This paper first examines different national policies (eg, in Canada, USA, France and the UK) to map the diversity of approaches regarding transplantation for FNs, and then works through different considerations commonly used to support or oppose the provision of organs to these patients: (1) the organ shortage; (2) the free-rider problem; (3) the risk of becoming a transplant destination; (4) the impact on organ donation rates; (5) physicians’ duties; (6) economic concerns; (7) vulnerability. Using a Canadian case as a focus, and generalising through a review of various national policies, we analyse the arguments for and against transplantation for FNs with a view to bringing clarity to what is a sensitive political and clinical management issue. Our aim is to help transplant centres, clinicians and ethicists reflect on the merits of possible options, and the rationales behind them. (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)

People tend to be repulsed by the idea of cash markets in kidneys, but support the trading of kidneys through paired exchanges or chains. We reject anti-commodification accounts of this reaction and offer an egalitarian one. We argue that the morally significant difference between cash markets and kidney chains is that the former allow the wealthy greater access to kidneys, while the latter do not. The only problem with kidney chains is that they do not go far enough (...) in addressing equality concerns, and we show how the introduction of cash payments by the state could remedy this. (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)

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.

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)

Introduction: The having extremely detailed macroscopic anatomy knowledge of the present medicine literature has been result of the information accumulation throughout the hundreds years. The numerous science hero have contributed for this purpose. The scientists being ahead of his time by their knowledge and scientific perspective have contributed worthy to development process of medicine. -/- Materials and Methods: The chapters related to the kidney anatomy in El-Kânûn Fi’t-Tıbb was written by İbn-i Sînâ in the 11th century, Kitab-ı Teşrihü’l-Ebdan Min (...) e’t-Tıb is one of the first illustrated anatomy books that was written by Mansur b. Muhammed b. Ahmed in 14th century, Teşrih-ülEbdan ve Tercümânı Kıbale-i Feylesûfan is the first illustrated Turkish anatomy book that was written by Şemseddîn-i İtâkî in 17th century were evaluated. -/- Results: The informations were compared in three books and were interpreted by the present informations. These books have contributed to development of anatomy although some of the informations in them are faulted. -/- Conclusion: All three books are valuable in point of showing the development of medicine. The extensive evaluation of books which have important place in history of medicine will give valuable information about development process of medicine. (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)

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)

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)

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)

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)

Julian Koplin, drawing extensively on empirical data, has argued that vendors, even in well-regulated kidney markets, are likely to be significantly harmed. I contend that his reasoning to this conclusion is dangerously mistaken. I highlight two failures. First, Koplin is insufficiently attentive to the differences between existing markets and the regulated markets proposed by advocates. On the basis of this error, he wrongly concludes that many harms will persist even in a well-regulated system. Second, Koplin misunderstands the utilitarian assessment (...) of the market. He focuses on the costs and benefits of the transaction for the vendor. But, the relevant comparison is between an individual’s welfare across different courses of action, namely, vending and the nonvending alternative. Although Koplin’s empirically informed contribution is a welcome addition to this literature, the mistakes that pervade his interpretation of the data demand correction. (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)

Abstract: In this study, we explore the challenge of identifying and preventing diseases in apple trees, which is a popular activity but can be difficult due to the susceptibility of these trees to various diseases. To address this challenge, we propose the use of Convolutional Neural Networks, which have proven effective in automatically detecting plant diseases. To validate our approach, we use images of apple leaves, including Apple Rot Leaves, Leaf Blotch, Healthy Leaves, and Scab Leaves collected (...) from Kaggle which is part from the Plant Village dataset. We generate a comprehensive training dataset using techniques such as image filtering, compression, and generation. Our model achieves impressive accuracy scores for all classes, with an overall accuracy of 99.93% on a dataset of 10,000 labeled images . (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)

In the absence of kidney markets, alternative institutions for exchanging kidneys have arisen to give donors incentives to donate. I examine thirteen such institutions, and ask whether moral arguments against markets, such as commodification, apply to them or not. I find that most arguments against kidney arguments also argue against these alternative institutions, meaning those arguments are not strong enough to prevent society from using institutions to exchange kidneys. Two arguments that do explain which kidney exchange institutions (...) are socially accepted and which are not are that institutions should not be want-regarding and should not be exploitative.Screening donors to eliminate those with socially unacceptable motives for donation and those who are in a position of being exploited could make kidney markets acceptable, since they would then only be vulnerable to arguments which have not prevented alternative exchange institutions from functioning. (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)

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)

In this article, I will reconstruct the monocausal model and argue that modern 'multifactorial diseases' are not monocausal by definition. 'Multifactorial diseases' are instead defined according to a constitutive disease model. On closer analysis, infectious diseases are also defined using the constitutive model rather than the monocausal model. As a result, our classification models alone cannot explain why infectious diseases have a universal etiology while chronic and noncommunicable diseases lack one. The explanation is instead provided (...) by the nineteenth-century germ theorists. (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)

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)

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)

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)

We recently suggested that there are both pragmatic and normative reasons to classify pregnancy as a disease. Several scholars argued against our claims. In this response, we defend the disease view of pregnancy against their criticism. We claim that the dysfunctional account of disease that some of our critics rely on has some counterintuitive results. Furthermore, we claim that our critics assume what needs to be argued that the primary function of our sexual organs is to reproduce. Since only a (...) small percentage of sexual intercourse leads to pregnancy, it is far from obvious that reproduction is the primary biological function of our sexual organs. We also claim that while taking pregnancy itself as a reference class could avoid the conclusion that pregnancy is a disease, the strategy is problematic since it renders the Boorsean approach to disease and health circular and effectively deprives it of any utility in determining whether a particular phenomenon is a disease or not. (shrink)

Last year saw the 20th anniversary edition of JECP, and in the introduction to the philosophy section of that landmark edition, we posed the question: apart from ethics, what is the role of philosophy ‘at the bedside’? The purpose of this question was not to downplay the significance of ethics to clinical practice. Rather, we raised it as part of a broader argument to the effect that ethical questions – about what we should do in any given situation – are (...) embedded within whole understandings of the situation, inseparable from our beliefs about what is the case, what it is that we feel we can claim to know, as well as the meaning we ascribe to different aspects of the situation or to our perception of it. Philosophy concerns fundamental questions: it is a discipline requiring us to examine the underlying assumptions we bring with us to our thinking about practical problems. Traditional academic philosophers divide their discipline into distinct areas that typically include logic: questions about meaning, truth and validity; ontology: questions about the nature of reality, what exists; epistemology: concerning knowledge; and ethics: how we should live and practice, the nature of value. Any credible attempt to analyse clinical reasoning will require us to think carefully about these types of question and the relationships between them, as they influence our thinking about specific situations and problems. So, the answers to the question we posed, about the role of philosophy at the bedside, are numerous and diverse, and that diversity is illustrated in the contributions to this thematic edition. (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)

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)

The highly contagious 2019 novel coronavirus disease (COVID-19) outbreak has not only impacted health systems, economies, and governments, it has also rapidly grown into a global health crisis, which is now threatening the lives of millions of people globally. While, on one hand, medical institutions are critically attempting to find a cure, on the other hand, governments have introduced striking measures and policies to curtail the rapid spread of the disease. Although COVID-19 has achieved pandemic status and is predominantly viewed (...) as a biomedical issue, it is argued that it should also be treated as a psychological crisis. This paper also reviews the literature to examine and comment on the detrimental effects of isolation, which has been enforced as one of the primary preventative measures to manage the spread of COVID-19. This paper further outlines key recommendations that should be addressed across different levels to buffer against the known adverse effects of isolation, which is especially relevant for the current COVID-19 situation, where a large proportion of the global population is isolated, confined, and/or quarantined. (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)

Background: The castor bean is a large grassy or semi-wooden shrub or small tree. Any part of the castor plant parts can suffering from a disease that weakens the ability to grow and eliminates its production. Therefore, in this paper will identify the pests and diseases present in castor culture and detect the symptoms in each disease. Also images is showing the symptom form in this disease. Objectives: The main objective of this expert system is to obtain appropriate diagnosis (...) of the disease. Methods: In this paper, the expert system is designed for the ability of agricultural engineers to detect and diagnose disease of castor like as: seeding blight, alternaria blight, cercospora leaf spot, powdery mildew and wilt. This system presents the disease symptoms, survival and spread, favorable conditions and image for each disease. Clips and Delphi expert system languages are used for designing and implementing the proposed expert system. Results: The expert system in the diagnosis of castor diseases was assessed by farmers and agricultural engineers and they were satisfied and accepted with its quality of performance. Conclusions: The expert system is easy for farmers and people have experience in the plant of castor to detect and diagnosis the symptoms that may face this plant from several disease. (shrink)

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

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)