Most regulations and guidelines require that potential research participants be told a great deal of information during the consent process. Many of these documents, and most of the scholars who consider the consent process, assume that all this information must be disclosed because it must all be understood. However, a wide range of studies surveying apparently competent participants in clinical trials around the world show that many do not understand key aspects of what they have been told. The standard (...) view of the conditions for valid consent therefore implies that these people have failed to give valid consent to research participation. In this paper we argue that the standard view is false. The primary function of the requirement that researchers disclose information about a study is the avoidance of illegitimate control over someone’s consent decision, which is a form of fraud.We derive the content and manner of appropriate disclosure by analysing the ways in which the manipulation of information can invalidate consent. Our analysis shows that the informational requirements for valid consent are conceptually distinct and thus unlikely to have identical contents. This implies that consent can be valid when not everything that ought to be disclosed by the person asking for consent is understood by the person who proffers it. (shrink)

Bradford Hill (1965) highlighted nine aspects of the complex evidential situation a medical researcher faces when determining whether a causal relation exists between a disease and various conditions associated with it. These aspects are widely cited in the literature on epidemiological inference as justifying an inference to a causal claim, but the epistemological basis of the Hill aspects is not understood. We offer an explanatory coherentist interpretation, explicated by Thagard's ECHO model of explanatory coherence. The ECHO model captures the (...) complexity of epidemiological inference and provides a tractable model for inferring disease causation. We apply this model to three cases: the inference of a causal connection between the Zika virus and birth defects, the classic inference that smoking causes cancer, and John Snow’s inference about the cause of cholera. (shrink)

An axiom of medical research ethics is that a protocol is moral only if it has a “favorable risk-benefit ratio”. This axiom is usually interpreted in the following way: a medical research protocol is moral only if it has a positive expected value -- that is, if it is likely to do more good (to both subjects and society) than harm. I argue that, thus interpreted, the axiom has two problems. First, it is unusable, because it (...) requires us to know more about the potential outcomes of research than we ever could. Second, it is false, because it conflicts with the so-called “soft paternalist” principles of liberal democracy. In place of this flawed rule I propose a new way of making risk-benefit assessments, one that does comport with the principles of liberalism. I argue that a protocol is moral only if it would be entered into by competent subjects who are informed about the protocol. The new rule this eschews all pseudo-utilitarian calculation about the protocol’s likely harms and benefits. (shrink)

It is unknown to what extent medical researchers generalize study findings beyond their samples when their sample size, sample diversity, or knowledge of conditions that support external validity do not warrant it. It is also unknown to what extent medical researchers describe their results with precise quantifications or unquantified generalizations, i.e., generics, that can obscure variations between individuals. We therefore systematically reviewed all prospective studies (n = 533) published in the top four highest ranking medical journals, Lancet, (...) New England Journal of Medicine (NEJM), Journal of the American Medical Association (JAMA), and the British Medical Journal (BMJ), from January 2022 to May 2023. We additionally reviewed all NEJM Journal Watch clinical research summaries (n = 143) published during the same time. Of all research articles reporting prospective studies, 52.5% included generalizations beyond specific national study populations, with the numbers of articles with generics varying significantly between journals (JAMA = 12%; Lancet = 77%) (p < 0.001, V = 0.48). There was no evidence that articles containing broader generalizations or generics were correlated with larger or more nationally diverse samples. Moreover, only 10.2% of articles with generalizations beyond specific national populations reported external validity strengthening factors that could potentially support such extrapolations. There was no evidence that original research articles and NEJM Journal Watch summaries intended for practitioners differed in their use of broad generalizations, including generics. Finally, from the journal with the highest citation impact, articles containing broader conclusions were correlated with more citations. Since there was no evidence that studies with generalizations beyond specific national study populations or with generics were associated with larger, more nationally diverse samples, or with reports of population similarity that may permit extensions of conclusions, our findings suggest that the generalizations in many articles were insufficiently supported. Caution against overly broad generalizations in medical research is warranted. (shrink)

Mainstream views of medical research tell us it should be a fact-based, value-free endeavor: what a scientist (or her funding source) wants or cares about should not influence her findings. At the same time, we also sometimes criticize medical research for failing to embody certain values, e.g. when we criticize pharmaceutical companies for largely ignoring the diseases that affect the global poor. This chapter seeks to reconcile these perspectives by distinguishing appropriate from inappropriate influences of values (...) on medical research. It divides this broad question into two narrower ones, the Role Question (at what points in the research process is value influence potentially acceptable?) and the Content Question (when value influence is potentially acceptable, what specific values should researchers use?), and then draws on the philosophical literature on values in science to explore answers to each of them. (shrink)

Hysteria, a mysterious disease known since antiquity, is said to have ceased to exist. Challenging this commonly held view, this is the first cross-disciplinary study to examine the current functional neuroimaging research into hysteria and compare it to the nineteenth-century image-based research into the same disorder. Paula Muhr's central argument is that, both in the nineteenth-century and the current neurobiological research on hysteria, images have enabled researchers to generate new medical insights. Through detailed case studies, Muhr (...) traces how different images, from photography to functional brain scans, have reshaped the historically situated medical understanding of this disorder that defies the mind-body dualism. (shrink)

As a result of the world-wide COVID-19 epidemic, an internal tension in the goals of medicine has come to the forefront of public debate. Medical professionals are continuously faced with a tug of...

Background: The internationalization of clinical studies requires a shared understanding of the fundamental ethical values guiding clinical studies. It is important that these values are not only embraced at the legal level but also adopted by clinicians themselves during clinical studies. Objective: Our goal is to provide an insight on how clinicians in Germany and Poland perceive and identify the different ethical issues regarding informed consent in clinical studies. Methods: To gain an understanding of how clinicians view clinical studies in (...) the countries they work in, we carried out semi-structured problem-centered interviews per telephone in Poland (n = 6) and Germany (n = 6). Our interviewees concentrated on three main topics: an appraisal of the normative framework, challenges in the information process and the protection of all participants in clinical studies. Results: Clinicians generally supported the normative framework, even though they considered it quite complex. In the two study countries, a widely noted dilemma in the information process was whether to overburden participants with extensive information or risking leaving out important facts. Clinicians were ready to exclude larger population groups from participating in clinical studies when the information process could not be carried out with standard procedures or when their inclusion was ethically sensitive. Conclusion: Clinicians need to gain a better understanding of the consequences of excluding larger population groups form participating in clinical studies. They should seek assistance in improving the information process for the inclusion of underrepresented groups in clinical studies. (shrink)

Smajdor argues that “recognition” is the solution to the “reifying attitude” that results from “the urge to protect ‘vulnerable’ people through exclusion from research”. Drawing on theories of reification, we argue that it is the concepts of autonomy and vulnerability themselves that have been reified, resulting in the impoverishment of approaches to autonomy at law and in research ethics. Overcoming such reification demands a deeper consideration of the grounds on which vulnerable individuals are owed recognition and thereby the (...) forms such recognition should take. Smajdor argues for a recognition that appeals to autonomy and that manifests in providing vulnerable individuals with the opportunity to assent. The problem is that this kind of recognition is dependent on a more fundamental kind. It is this second form of recognition that would need to do the heavy lifting for assent-based frameworks to avoid the same problems we find with consent. (shrink)

Cho and Martinez-Martin provide a wide-ranging analysis of what they label “digital simulacra”—which are in essence data-driven AI-based simulation models such as digital twins or models used for i...

The case study presented by Winch and Sinnott (2011) shows not only how difficult it is for clinicians and researchers to identify conflicts of interest (COI), but also how damaging it can be when there are unin- formed and uncoordinated policy responses by senior administrators.

This book examines the moral luck paradox, relating it to Kantian, consequentialist and virtue-based approaches to ethics. It also applies the paradox to areas in medical ethics, including allocation of scarce medical resources, informed consent to treatment, withholding life-sustaining treatment, psychiatry, reproductive ethics, genetic testing and medical research. If risk and luck are taken seriously, it might seem to follow that we cannot develop any definite moral standards, that we are doomed to moral relativism. However, Dickenson (...) offers strong counter-arguments to this view that enable us to think in terms of universal standards. (shrink)

Consensus statement by UK teachers of medical ethics and law.

There is a lot of conceptual engineering going on in medical research. I substantiate this claim with two examples, the medical debate about cancer classification and about obesity as a disease I also argue that the proper target of conceptual engineering in medical research are experts’ conceptions. These are explicitly written down in documents and guidelines, and they bear on research and policies. In the second part of the chapter, I propose an externalist framework (...) in which conceptions have both the explanatory power of psychological concepts and that of semantic concepts. It is likely, however, that human activities and practices distinct from medical research, and regulated by different practices and epistemic rules, call for different targets for conceptual engineering. I conclude with indicating an open agenda of problems for philosophers of medicine interested in conceptual engineering. (shrink)

This article argues that personal medical data should be made available for scientific research, by enabling and encouraging individuals to donate their medical records once deceased, similar to the way in which they can already donate organs or bodies. This research is part of a project on posthumous medical data donation developed by the Digital Ethics Lab at the Oxford Internet Institute at the University of Oxford. Ten arguments are provided to support the need to (...) foster posthumous medical data donation. Two major risks are also identified—harm to others, and lack of control over the use of data—which could follow from unregulated donation of medical data. The argument that record-based medical research should proceed without the need to secure informed consent is rejected, and instead a voluntary and participatory approach to using personal medical data should be followed. The analysis concludes by stressing the need to develop an ethical code for data donation to minimise the risks, and offers five foundational principles for ethical medical data donation suggested as a draft code. (shrink)

There have recently been novel applications of medical systematic review guidelines to economic policy interventions which contain controversial methodological assumptions that require further scrutiny. A landmark 2017 Cochrane review of unconditional cash transfer (UCT) studies, based on the Grading of Recommendations Assessment, Development and Evaluation (GRADE), exemplifies both the possibilities and limitations of applying medical systematic review guidelines to UCT and universal basic income (UBI) studies. Recognizing the need to upgrade GRADE to incorporate the differences between medical (...) and policy interventions, the GRADE Public Health Project Group (PHPG) was convened to enumerate and address these methodological challenges. However, in light of our analysis of additional methodological challenges that arise for UCT and UBI studies, we argue that the adaptation of medical systematic review guidelines to economic methodology is far from straightforward and is in fact more challenging than claimed by the PHPG. (shrink)

Assumptions about obesity—e.g., its connection to ill health, its causes, etc.—are still prevalent today, and they make up what I call the medical model of fatness. In this paper, I argue that the medical model was established on the basis of insufficient evidence and has nevertheless continued to be relied upon to justify methodological choices that further entrench the assumptions of the medical model. These choices are illegitimate in so far as they conflict with both the epistemic (...) and social aims of obesity research. I conclude the paper with a partial solution to these epistemic and social shortcomings. (shrink)

In medical settings, machines are in close proximity with human beings: with patients who are in vulnerable states of health, who have disabilities of various kinds, with the very young or very old, and with medical professionals. Machines in these contexts are undertaking important medical tasks that require emotional sensitivity, knowledge of medical codes, human dignity, and privacy. -/- As machine technology advances, ethical concerns become more urgent: should medical machines be programmed to follow a (...) code of medical ethics? What theory or theories should constrain medical machine conduct? What design features are required? Should machines share responsibility with humans for the ethical consequences of medical actions? How ought clinical relationships involving machines to be modeled? Is a capacity for empathy and emotion detection necessary? What about consciousness? -/- The essays in this collection by researchers from both humanities and science describe various theoretical and experimental approaches to adding medical ethics to a machine, what design features are necessary in order to achieve this, philosophical and practical questions concerning justice, rights, decision-making and responsibility, and accurately modeling essential physician-machine-patient relationships. -/- This collection is the first book to address these 21st-century concerns. (shrink)

Abstract: The integration of Artificial Intelligence (AI) into medical imaging represents a transformative shift in healthcare, offering significant improvements in diagnostic accuracy, efficiency, and patient outcomes. This paper explores the application of AI technologies in the analysis of medical images, focusing on techniques such as convolutional neural networks (CNNs) and deep learning models. We discuss how these technologies are applied to various imaging modalities, including X-rays, MRIs, and CT scans, to enhance disease detection, image segmentation, and diagnostic support. (...) Additionally, the paper addresses the challenges faced in AI-driven medical imaging, including data quality, model interpretability, and ethical considerations. By examining recent advancements and real-world case studies, this paper provides insights into the current state of AI in medical imaging and its potential future directions. The findings highlight the ongoing evolution of AI technologies and their crucial role in advancing medical diagnostics and treatment strategies. (shrink)

Medical tourism can be defined as the process of travelling outside of an individual’s country to another to seek medical care. The current research studies medical tourism in Ghana historically, focusing on Korle Bu Teaching Hospital in Accra and Komfo Anokye Teaching Hospital in Kumase. Using a qualitative research approach, the study provides a historical argument on the continuities and discontinuities of medical tourism in Ghana. Indeed, medical tourism has undergone several transitions over (...) time. To emphasize, the current contribution has thoroughly discussed the evolution of medical tourism in Ghana, the pull and push factors of medical tourism, its impact on the local health systems and the need to further promote it. The study concludes among other things that the improvement of medical facilities, personnel and equipment, will enhance the medical tourism prospects of the country. (shrink)

: The Islamic jurists utilized the discipline of maqāṣid al-sharīʿah,in its capacity as the philosophy of Islamic law, in their legal and ethicalinterpretations, with added interest in addressing the issues of modern times.Aphoristically subsuming the major themes of the Sharīʿah, maqāṣid play apivotal role in the domain of decision-making and deduction of rulings onunprecedented ethical discourses. Ethics represent the infrastructure of Islamiclaw and the whole science of Islamic jurisprudence operates in the lightof maqāṣid to realize the ethics in people’s lives. (...) Scrutinizing the key themesof maqāṣid-based ijtihād and scope of ethics in maqāṣid, this article delvesinto the discourse on the application of maqāṣid to medical ethics. As a casestudy, this research analyses the extent of medical confidentiality in the light ofmaqāṣid and arrives at the conclusion that limited confidentiality goes more inline with the maxims of maqāṣid. (shrink)

Most people are completely oblivious to the danger that their medical data undergoes as soon as it goes out into the burgeoning world of big data. Medical data is financially valuable, and your sensitive data may be shared or sold by doctors, hospitals, clinical laboratories, and pharmacies—without your knowledge or consent. Medical data can also be found in your browsing history, the smartphone applications you use, data from wearables, your shopping list, and more. At best, data about (...) your health might end up in the hands of researchers on whose good will we depend to avoid abuses of power.2 Most likely, it will end up with data brokers who might sell it to a future employer, or an insurance company, or the government. At worst, your medical data may end up in the hands of criminals eager to commit extortion or identity theft. In addition to data harms related to exposure and discrimination, the collection of sensitive data by powerful corporations risks the creation of data monopolies that can dominate and condition access to health care. -/- This chapter aims to explore the challenge that big data brings to medical privacy. Section I offers a brief overview of the role of privacy in medical settings. I define privacy as having one’s personal information and one’s personal sensorial space (what I call autotopos) unaccessed. Section II discusses how the challenge of big data differs from other risks to medical privacy. Section III is about what can be done to minimise those risks. I argue that the most effective way of protecting people from suffering unfair medical consequences is by having a public universal healthcare system in which coverage is not influenced by personal data (e.g., genetic predisposition, exercise habits, eating habits, etc.). (shrink)

In contemporary healthcare, medical image categorization is essential for illness prediction, diagnosis, and therapy planning. The emergence of digital imaging technology has led to a significant increase in research into the use of machine learning (ML) techniques for the categorization of images in medical data. We provide a thorough summary of recent developments in this area in this review, using knowledge from the most recent research and cutting-edge methods.We begin by discussing the unique challenges and opportunities (...) associated with medical image classification, including the complexity of anatomical structures, variability in imaging modalities, and the need for interpretability and reliability in clinical settings. Subsequently, we survey a wide range of ML algorithms and techniques employed for medical image classification, including traditional methods such as support vector machines and k-nearest neighbors, as well as deep learning approaches like convolutional neural networks (CNNs) and recurrent neural networks (RNNs). Furthermore, we examine key considerations in dataset preparation, feature extraction, and model evaluation specific to medical image classification tasks. We highlight the importance of large, annotated datasets, transfer learning, and data augmentation techniques in enhancing model performance and generalization. (shrink)

Pain medication is one of the responses to the mercy argument that utilitarian ethicists use for justifying active euthanasia on the grounds of prevention of cruelty and appeal to beneficence. The researcher reinforces the significance of pain medication in meeting this challenge and considers it the most preferred response among various other responses. It is because of its realism and effectiveness. In exploring the mechanism and considerations related to pain medication, the researcher briefly touches the Catholic ethical position on the (...) issue, a position that cannot be ignored in the development of contemporary bioethics. The researcher particularly deliberates on the contemporary Islamic discourse on the issue; by furthering the debate in line with the Islamic legal maxims and general guidance from the primary sources of Islamic law and ethics. The resolution on the issue is sought by synthesizing the views and legal maxims (al-Qawaid al-Fiqhiyyah) on the issue, which in conclusion provide justification for pain medication by considerably regarding pain as necessity and pressing need. However, such resolution allows pain medication to the limit and proportion that removes the pain and prohibits overdosing the patient with medication that may directly cause the death. (shrink)

Although ethics is an essential component of undergraduate medical education, research suggests current medical ethics curricula face considerable challenges in improving students’ ethical reasoning. This paper discusses these challenges and introduces a promising new mode of graduate and professional ethics instruction for overcoming them. We begin by describing common ethics curricula, focusing in particular on established problems with current approaches. Next, we describe a novel method of ethics education and assessment for medical students that we have (...) devised, the Medical Ethics Bowl. Finally, we suggest pedagogical advantages to MEBs when compared to other ethics curricula. (shrink)

Current challenges in medical practice, research, and administration demand physicians who are familiar with bioethics, health law, and health economics. Curriculum directors at American Association of Medical Colleges-affiliated medical schools were sent confidential surveys requesting the number of required hours of the above subjects and the years in which they were taught, as well as instructor names. The number of relevant publications since 1990 for each named instructor was assessed by a PubMed search.In sum, teaching in (...) all three subjects combined comprises less than two percent of the total hours in the American medical curriculum, and most instructors have not recently published articles in the fields they teach. This suggests that medical schools should reevaluate their curricula and instructors in bioethics, health law, and health economics. (shrink)

Biomedical science has been remarkably successful in explaining illness by categorizing diseases and then by identifying localizable lesions such as a virus and neoplasm in the body that cause those diseases. Not surprisingly, researchers have aspired to apply this powerful paradigm to addiction. So, for example, in a review of the neuroscience of addiction literature, Hyman and Malenka (2001, p. 695) acknowledge a general consensus among addiction researchers that “[a]ddiction can appropriately be considered as a chronic medical illness.” Like (...) other diseases, “Once addiction has taken hold, it tends to follow a chronic course.” (Koob and La Moal 2006, p. ?). Working from this perspective, much effort has gone into characterizing the symptomology of addiction and the brain changes that underlie them. Evidence for involvement of dopamine transmission changes in the ventral tegmental area (VTA) and nucleus accumbens (NAc) have received the greatest attention. Kauer and Malenka (2007, p. 844) put it well: “drugs of abuse can co-opt synaptic plasticity mechanisms in brain circuits involved in reinforcement and reward processing”. Our goal in this chapter to provide an explicit description of the assumptions of medical models, the different forms they may take, and the challenges they face in providing explanations with solid evidence of addiction. <br>. (shrink)

In a recent Response published in the Journal of Medical Ethics,1 Buturovic provides two criticisms of my argument in ‘Is the exclusion of psychiatric patients from access to physician-assisted suicide discriminatory?’2 First, Buturovic argues that my argument effectively ‘erases the distinction between healthy adults and patients (whether somatic or psychiatric) essentially implying that PAS [physician-assisted suicide] should be available to all, for all reasons or, ultimately no reason’ (Buturovic,1 pg. 1). Second, Buturovic argues that opening the doors to (...) class='Hi'>medical assistance in dying (MAID) for psychiatric patients could have a number of undesirable implications. In particular, Buturovic highlights the potential negative implications for relations of trust in medicine—psychiatry in particular—along with potential effects on the rate of organ donation. I would here like to respond to these two criticisms. In short, my response to Buturovic’s first argument is that the slope is not nearly as slippery as Buturovic suggests. The reason for this is that the plausibility of Buturovic’s argument rests on a significant misinterpretation of my argument, along with an important equivocation in her own. Buturovic argues that, under the three criteria that I propose for the provision of MAID—sufficient decision-making capacity, demonstrated treatment resistance, and a lack of substantially negative implications for existing standards of psychiatric treatment and research—the provision of MAID for trivial reasons, even no reason at all, is justifiable. The main problem with this argument is that I propose no such positive criteria. My argument is that none of the three arguments addressed in my previous paper are sufficient to justify the exclusion of any and all psychiatric patients from access to MAID. I do not claim, in other words, that any individual …. (shrink)

Forms of Artificial Intelligence (AI) are already being deployed into clinical settings and research into its future healthcare uses is accelerating. Despite this trajectory, more research is needed regarding the impacts on patients of increasing AI decision making. In particular, the impersonal nature of AI means that its deployment in highly sensitive contexts-of-use, such as in healthcare, raises issues associated with patients’ perceptions of (un) dignified treatment. We explore this issue through an experimental vignette study comparing individuals’ perceptions (...) of being treated in a dignified and respectful way in various healthcare decision contexts. Participants were subject to a 2 (human or AI decision maker) x 2 (positive or negative decision outcome) x 2 (diagnostic or resource allocation healthcare scenario) factorial design. We found evidence of a “human bias” (i.e., a preference for human over AI decision makers) and an “outcome bias” (i.e., a preference for positive over negative outcomes). However, we found that for perceptions of respectful and dignified interpersonal treatment, it matters more who makes the decisions in diagnostic cases and it matters more what the outcomes are for resource allocation cases. We also found that humans were consistently viewed as appropriate decision makers and AI was viewed as dehumanizing, and that participants perceived they were treated better when subject to diagnostic as opposed to resource allocation decisions. Thematic coding of open-ended text responses supported these results. We also outline the theoretical and practical implications of these findings. (shrink)

In a challenge trial, research subjects are purposefully exposed to some pathogen in a controlled setting, in order to test the efficacy of a vaccine or other experimental treatment. This is an example of medical effective altruism (MEA), where individuals volunteer to risk harms for the public good. Many bioethicists rejected challenge trials in the context of Covid‐19 vaccine research on ethical grounds. After considering various grounds of this objection, I conclude that the crucial question is how (...) much harm research subjects can permissibly risk. But we lack a satisfying way of making this judgment that does not appeal simply to the intuitions of doctors or bioethicists. I consider one recent and structurally plausible approach to critically evaluating the harm question. Alex London defends a social consistency test for research risks: we should compare the risks undertaken by research subjects to relevantly similar risks which are accepted in other spheres of society. I argue there is no good reason not to consider volunteer military service as a relevant social comparison. This implies there is essentially no cap on acceptable risks on the social consistency rationale. In short, if soldiers can be heroes, why can't research volunteers? (shrink)

Modern health care relies extensively on the use of technologies for assessing and treating patients, so it is important to be certain that health care technologies perform their professed functions in an effective and safe manner. Philosophers of technology have developed methods to assign and evaluate the functions of technological products, the major elements of which are described in the ICE theory. This paper questions whether the standard of evidence advocated by the ICE theory is adequate for ascribing and assessing (...) technologies employed in health care. The paper proposes that the general problem with the standard of evidence embodied in the ICE theory is too permissive for assessing medical technologies, in that it does not take into account the relative benefit and harm of medical technologies in ensuring safe functional performance in patients. The paper illustrates how evidence-based medicine has demonstrated the value of clinical research methods, including observational studies, randomized and non-randomized clinical trials, and formal techniques, such as meta-analysis, to measure therapeutic effectiveness. I argue, therefore, that evidence from clinical research studies should take precedence over the testimonial evidence and other types of non-clinical evidence, in providing justification for health technologies. (shrink)

The European Medical Information Framework project, funded through the IMI programme, has designed and implemented a federated platform to connect health data from a variety of sources across Europe, to facilitate large scale clinical and life sciences research. It enables approved users to analyse securely multiple, diverse, data via a single portal, thereby mediating research opportunities across a large quantity of research data. EMIF developed a code of practice to ensure the privacy protection of data subjects, (...) protect the interests of data sharing parties, comply with legislation and various organisational policies on data protection, uphold best practices in the protection of personal privacy and information governance, and eventually promote these best practices more widely. EMIF convened an Ethics Advisory Board, to provide feedback on its approach, platform, and the EcoP. The most important challenges the ECoP team faced were: how to define, control and monitor the purposes for which federated health data are used; the kinds of organisation that should be permitted to conduct permitted research; and how to monitor this. This manuscript explores those issues, offering the combined insights of the EAB and EMIF core ECoP team. For some issues, a consensus on how to approach them is proposed. For other issues, a singular approach may be premature but the challenges are summarised to help the community to debate the topic further. Arguably, the issues and their analyses have application beyond EMIF, to many research infrastructures connected to health data sources. (shrink)

The Medical bot project is built using artificial algorithms that analyses user’s queries and understand user’s message. This System is a web application which provides answer to the query of the patients. Patients just have to query through the bot which is used for chatting. Patients can chat using any format there is no specific format the user has to follow. The System uses built in artificial intelligence to answer the query. The answers are appropriate what the user queries. (...) The User can query any Medical related activities through the system. The user does not have to personally go to the Medical for enquiry. The System analyses the question and then answers to the user. The system answers to the query as if it is answered by the person. With the help of artificial intelligence, the system answers the query asked by the patients. The system replies using an effective Graphical user interface which implies that as if a real person is talking to the user. The user just has to register himself to the system and has to login to the system. After login user can access to the various helping pages. Various helping pages has the bot through which the user can chat by asking queries related to Medical activities. The system replies to the user with the help of effective graphical user interface. The user can query about the Medical related activities through online with the help of this web application. The user can query Medical related activities such as date and timing of annual day, sports day, and other cultural activities. This system helps the patients to be updated about the Medical activities. (shrink)

Background Professional communities such as the medical community are acutely concerned with negligence: the category of misconduct where a professional does not live up to the standards expected of a professional of similar qualifications. Since science is currently strengthening its structures of self-regulation in parallel to the professions, this raises the question to what extent the scientific community is concerned with negligence, and if not, whether it should be. By means of comparative analysis of medical and scientific codes (...) of conduct, we aim to highlight the role of negligence provisions in codes of conduct for scientists, and to discuss the normative consequences for future codes of conduct. -/- Methods We collected scientific and medical codes of conduct in a selection of OECD countries, and submitted each code of conduct to comparative textual analysis. -/- Results Negligence is invariably listed as an infraction of the norms of integrity in medical codes of conduct, but only rarely so in the scientific codes. When the latter list negligence, they typically do not provide any detail on the meaning of ‘negligence’. -/- Discussion Unlike codes of conduct for professionals, current codes of conduct for scientists are largely silent on the issue of negligence, or explicitly exclude negligence as a type of misconduct. In the few cases where negligence is stipulated to constitute misconduct, no responsibilities are identified that would help prevent negligence. While we caution against unreasonable negligence provisions as well as disproportionate sanctioning systems, we do argue that negligence provisions are crucial for justified trust in the scientific community, and hence that there is a very strong rationale for including negligence provisions in codes of conduct. (shrink)

Some patients, following brain injury, do not outwardly respond to spoken commands, yet show patterns of brain activity that indicate responsiveness. This is “cognitive-motor dissociation” (CMD). Recent research has used machine learning to diagnose CMD from electroencephalogram (EEG) recordings. These techniques have high false discovery rates, raising a serious problem of inductive risk. It is no solution to communicate the false discovery rates directly to the patient’s family, because this information may confuse, alarm and mislead. Instead, we need a (...) procedure for generating case-specific probabilistic assessments that can be communicated clearly. This article constructs a possible procedure with three key elements: (1) a shift from categorical “responding or not” assessments to degrees of evidence; (2) the use of patient-centred priors to convert degrees of evidence to probabilistic assessments; and (3) the use of standardized probability yardsticks to convey those assessments as clearly as possible. (shrink)

Abstract: In this research, the Artificial Neural Network (ANN) model was developed and tested to predict the rate of treatment expenditure on an individual or family in a country. A number of factors have been identified that may affect treatment expenses. Factors such as age, grade level such as primary, preparatory, secondary or college, sex, size of disability, social status, and annual medical expenses in fixed dollars excluding dental and outpatient clinics among others, as input variables for the (...) ANN model. A model based on the multi-layer Perceptron topology was developed and trained using data on 5574 cases. The evaluation of the test data shows that the ANN model is capable of predicting correctly Medical Expenses. (shrink)

In critical medical emergencies, timely and accurate drug recommendation is essential for saving lives and reducing complications. This project proposes a Drug Recommendation System utilizing Machine Learning (ML) techniques to assist healthcare professionals in making quick and accurate drug selections based on patient symptoms, medical history, and emergency condition. The system integrates data from diverse medical databases, including symptoms, diseases, patient demographics, and prior medical records, to recommend the most appropriate drugs or treatments in real-time. The (...) ML model is trained on historical medical data, utilizing algorithms such as Decision Trees, Random Forests, and Neural Networks to predict optimal drug choices for different emergency situations. The system not only considers the immediate medical needs but also factors in contraindications, potential drug interactions, and patient-specific conditions, ensuring safer drug administration. This approach aims to reduce human errors in emergency drug prescriptions, enhance the speed of medical response, and improve the overall quality of care during emergencies. By leveraging data-driven insights, the system supports healthcare professionals in making well-informed decisions, even in high-pressure situations. Ultimately, the Drug Recommendation System serves as a valuable tool in healthcare, enhancing emergency medical care and optimizing treatment outcomes. (shrink)

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

Background: Community-based education (CBE) involves educating the head (cognitive), heart (affective), and the hand (practical) by utilizing tools that enable us to broaden and interrogate our value systems. This article reports on the use of virtue ethics (VE) theory for understanding the principles that create, maintain and sustain a socially accountable community placement programme for undergraduate medical students. Our research questions driving this secondary analysis were; what are the goods which are internal to the successful practice of CBE (...) in medicine, and what are the virtues that are likely to promote and sustain them? -/- Methods: We conducted a secondary theoretically informed thematic analysis of the primary data based on MacIntyre’s virtue ethics theory as the conceptual framework. -/- Results: Virtue ethics is an ethical approach that emphasizes the role of character and virtue in shaping moral behavior; when individuals engage in practices (such as CBE), goods internal to those practices (such as a collaborative attitude) strengthen the practices themselves, but also augment those individuals’ virtues, and that of their community (such as empathy). We identified several goods that are internal to the practice of CBE and accompanying virtues as important for the development, implementation and sustainability of a socially accountable community placement programme. A service-oriented mind-set, a deep understanding of community needs, a transformed mind, and a collaborative approach emerged as goods internal to the practice of a socially accountable CBE. The virtues needed to sustain the identified internal goods included empathy and compassion, connectedness, accountability, engagement [sustained relationship], cooperation, perseverance, and willingness to be an agent of change. -/- Conclusion: This study found that MacIntyre’s virtue ethics theory provided a useful theoretical lens for understanding the principles that create, maintain and sustain CBE practice. (shrink)

Today's realities require medical institutions to take more careful account of intangible factors that make up an irreplaceable component of cultural characteristics. Changes in the socio-economic conditions of economic activity have led to increased attention of the management of medical institutions to the need to form a corporate style that will provide additional competitive advantages. The purpose of the study is to identify the functions and elements of the corporate style of a medical institution and its subdivisions, (...) to find out its impact on the collective consciousness and behavior of consumers of medical services and to establish requirements for its development. The methodological basis of the study is modern research on the formation of corporate style and its impact on the reputation and successful development of organizations. The main hypothesis of the study is the assumption that corporate style influences the level of recognition and authority of a medical institution. Summary of the main research material. It is proved that an authentic, working corporate style for a modern medical institution is a necessary element of its organizational culture. It is determined that the corporate style contributes to creating a positive image of a medical institution in the eyes of consumers; allows distinguishing a medical institution from other medical institutions with a similar range of services; strengthens the organizational spirit of medical staff; increases the effectiveness of advertising; and creates a favorable image of a medical institution. The originality and practical significance of the study lies in the fact that a comparative analysis of the elements of corporate style of city clinical hospitals in Dnipro, which are clearly implemented on the official pages on the Internet, was carried out. Conclusions and prospects for further research. The conducted research has made it possible to state that the considered medical institutions of the city of Dnipro do not pay the necessary attention to the formation of their own corporate style. Sporadic initiatives and events create the appearance of the existence of a corporate style of a medical institution, but do not ensure the existence of such a corporate style that would work to increase the recognition and authority of a medical institution. (shrink)

Education on authorship was delivered and evaluated by pre test and post test questionnairen on 30 post graduate medical students at the Department of Anestheology, Dhaka Medical College, Bangladesh between January and June 2019 to understand the knowledge, skill and attitude of post graduate medical students on authorship. Result: Before intervention, majority (60%) of the students felt that who perform the research work should be the author of the article. But 40% students were divided and felt (...) that who advised the design of the research (20%), who provided the grants (10%) and Chief/Head of the division (10%) should be the author of the article respectively. Maximum (70%) respondents did not know the order of authorship. Of 40% respondent felt that the PI should be always the first author and 40% don’t know the answer. Half of the students (50%) felt that keeping honorary author increased the opportunity of acceptance of publication. Of 36.7% and 13.3% of students felt that keeping honorary author increased the article’s value and made good relation to them to get some extra facility from them respectively. Of 20% participants were pressurized by lab head/head of department for inclusion of their name as an author. Half of the (56.7 %) respondents felt that the author’s contribution should be stated in the article. Only few 4 (13.3%) respondents said that their institute had guideline for authorship. However, after education 100% of students felt that who perform the research work should be only the author of the article. All (100%) respondents understood the order of authorship. Most of the students (86%) felt that PI should be always the first author. Of 100% respondent felt supervisor of the research should be the last author. All students (100%) felt author’s contribution should be mentioned in the article. All (100%) students did not want to include as author those who help in research design and secured grant; and they did not like to keep honorary author in their article. All (100%) students expressed that their institute had no guideline for authorship. After intervention, three groups of students were asked to write one page of article on Anesthesiology. Interestingly, they did not include any name in the author by line who were not participate or had any contribution in the writing. Conclusion: The comparative data between pre- and post-text have highlighted a general lack of understanding of the basic concept of authorship ethics which significantly improved after the intervention. The results also indicate that the education on authorship improved the awareness of postgraduate medical students in a particular centre. (shrink)

Medical terminology collects and organizes the many different kinds of terms employed in the biomedical domain both by practitioners and also in the course of biomedical research. In addition to serving as labels for biomedical classes, these names reflect the organizational principles of biomedical vocabularies and ontologies. Some names represent invariant features (classes, universals) of biomedical reality (i.e., they are a matter for ontology). Other names, however, convey also how this reality is perceived, measured, and understood by health (...) professionals (i.e., they belong to the domain of epistemology). We analyze terms from several biomedical vocabularies in order to throw light on the interactions between ontological and epistemological components of these terminologies. We identify four cases: 1) terms containing classification criteria, 2) terms reflecting detectability, modality, uncertainty, and vagueness, 3) terms created in order to obtain a complete partition of a given domain, and 4) terms reflecting mere fiat boundaries. We show that epistemology-loaded terms are pervasive in biomedical vocabularies, that the “classes” they name often do not comply with sound classification principles, and that they are therefore likely to cause problems in the evolution and alignment of terminologies and associated ontologies. (shrink)

Abstract: The integration of Artificial Intelligence (AI) into medical imaging marks a transformative advancement in healthcare, significantly enhancing diagnostic accuracy, efficiency, and patient outcomes. This paper delves into the application of AI technologies in medical image analysis, with a particular focus on techniques such as convolutional neural networks (CNNs) and deep learning models. We examine how these technologies are employed across various imaging modalities, including X-rays, MRIs, and CT scans, to improve disease detection, image segmentation, and diagnostic support. (...) Furthermore, the paper discusses the challenges associated with AI-driven medical imaging, such as data quality, model interpretability, and ethical considerations. By analyzing recent advancements and real-world case studies, this paper offers insights into the current landscape of AI in medical imaging and explores its potential future directions. The findings underscore the ongoing evolution of AI technologies and their pivotal role in advancing medical diagnostics and treatment strategies. (shrink)

The study aimed to identify the sharing of information and its impact on the quality of health care in Al-Shifa Medical Complex in the southern Palestinian governorates. The study adopted the descriptive analytical approach. The number is 2150 employees, and the questionnaire was distributed to a stratified random sample of 330 employees, and 302 questionnaires were retrieved, with a rate of 91.5%. One of the most important results of the study was that there is a statistically significant effect at (...) the level (α≤0.05) of information sharing for the performance of the medical staff in the quality of health care in Al-Shifa Medical Complex in the southern Palestinian governorates. The axis of participation in information came with a relative weight (69.6%) and a high degree. The level of health care quality was high with a relative weight of (69.0%). One of the most important recommendations of the study was the need to pay attention to measuring patients' satisfaction levels, and to set up a box for complaints and suggestions for patients, and what are their suggestions and point of view for the service provided to them. (shrink)

Nowadays, healthcare and medical education is qualified by test scores and competitiveness. This article considers its quality in terms of improving the moral competence of future healthcare providers. Objectives. Examining the relevance of moral competence in medico-clinical decision-making despite the paradigm shift and discussing the up-to-date findings on healthcare students. Design and method. N=115 participants were surveyed with a standard Moral Competence Test to examine how their moral competence development was affected by the learning environment and further important factors. (...) Results. The sample allowed the identification of a regress in moral competence during students’ pre-clinical curriculum, and progress during their clinical curriculum. A gender-related bias, a segmentation effect, and a pronunciation effect were noticed. Explanations. Scholarly literature usually reports a linear decrease of medical students’ C-scores resulting from, e.g., competitive trends in education. We identified such trends in terms of gender-specific competitive tactics. Religious and ethical affiliations were discussed to explain the unexpected gender bias and the related segmentation and pronunciation effects. The findings can be regarded as predictive for similar developments in educational institutions regardless of cultural contexts as the sample examined in this article represents medical education in a country facing a transition from a non-competitive to competitive tertiary education model, and between presecular and monocultural to secular and pluralist social ethics. (shrink)

Background: Besides regulatory learning skills, learning also requires students to relate to their social context and negotiate it as they transition and adjust to medical training. As such, there is a need to consider and explore the role of social and cultural aspects in student learning, particularly in problem-based learning, where the learning paradigm differs from what most students have previously experienced. In this article, we report on the findings of a study exploring first-year medical students’ experiences during (...) the first semester of an undergraduate problem-based learning medical program at an African medical school. Method: We employed a qualitative case study approach using in-depth interviews with 23 first-year medical students. Participants ranged in age from 18 to 25 years. All students were bi/multilingual (some spoke three to five languages), with English as the learning language. We conducted an inductive thematic analysis to systematically identify and analyze patterns in the data using the Braun and Clarke framework. Results: Before medical school, students worked hard to compete for admission to medical school, were primarily taught using a teacher-centered approach, and preferred working alone. At the beginning of medical school, students found it challenging to understand the problem-based learning process, the role of the case, speaking and working effectively in a group, managing a heavy workload, and taking increased responsibility for their learning. By the end of the first semester, most students were handling the workload better, were more comfortable with their peers and facilitators, and appreciated the value of the problem-based learning approach. Conclusions: Our study highlights the importance of interrogating contextual sociocultural factors that could cause tension when implementing problem-based learning in non-western medical schools. Adjustment to problem-based learning requires a conceptual and pedagogic shift towards learner-centered practice, particularly concerning self direction, the role of the case, and collaborative learning. As such, there is a need to develop and implement research informed learning development programs that enable students to reflect on their sociocultural beliefs and practices, and enhance their regulatory learning competence to optimize meaningful and early engagement with the problem based learning process. (shrink)

In the last two decades we have witnessed considerable efforts directed towards making electronic healthcare records comparable and interoperable through advances in record architectures and (bio)medical terminologies and coding systems. Deep semantic issues in general, and ontology in particular, have received some interest from the research communities. However, with the exception of work on so-called ‘controlled vocabularies’, ontology has thus far played little role in work on standardization. The prime focus has been rather the rapid population of terminologies (...) at the level of fine detail. In this paper, we argue that more efforts are needed on the side of both research and standardization to ensure that the coding systems used in electronic healthcare records enjoy a semantics that is coherent with the semantics of the record. We propose realist ontology as a method to bring about this coherence by means of a robust system of top-level ontological categories. (shrink)

Abstract: Artificial Intelligence (AI) is rapidly becoming a cornerstone of modern healthcare, offering unprecedented capabilities in diagnostics, treatment planning, patient care, and healthcare management. This paper explores the transformative impact of AI on the healthcare sector, examining how it enhances patient outcomes, improves the efficiency of medical practices, and introduces new ethical and operational challenges. By analyzing current applications such as AI-driven diagnostic tools, personalized medicine, and hospital management systems, this paper highlights the significant advancements AI has brought to (...) the field. However, the integration of AI also raises concerns related to data privacy, algorithmic bias, and the displacement of healthcare professionals. This study provides a comprehensive overview of these developments, offering insights into the future potential of AI in revolutionizing healthcare while addressing the ethical considerations that must accompany its adoption. The findings suggest that while AI holds the promise of transforming healthcare delivery, careful consideration of its implications is essential to ensure equitable and effective implementation. (shrink)

After long arguments between positivism and falsificationism, the verification of universal hypotheses was replaced with the confirmation of uncertain major premises. Unfortunately, Hemple proposed the Raven Paradox. Then, Carnap used the increment of logical probability as the confirmation measure. So far, many confirmation measures have been proposed. Measure F proposed by Kemeny and Oppenheim among them possesses symmetries and asymmetries proposed by Elles and Fitelson, monotonicity proposed by Greco et al., and normalizing property suggested by many researchers. Based on the (...) semantic information theory, a measure b* similar to F is derived from the medical test. Like the likelihood ratio, measures b* and F can only indicate the quality of channels or the testing means instead of the quality of probability predictions. Furthermore, it is still not easy to use b*, F, or another measure to clarify the Raven Paradox. For this reason, measure c* similar to the correct rate is derived. Measure c* supports the Nicod Criterion and undermines the Equivalence Condition, and hence, can be used to eliminate the Raven Paradox. An example indicates that measures F and b* are helpful for diagnosing the infection of Novel Coronavirus, whereas most popular confirmation measures are not. Another example reveals that all popular confirmation measures cannot be used to explain that a black raven can confirm “Ravens are black” more strongly than a piece of chalk. Measures F, b*, and c* indicate that the existence of fewer counterexamples is more important than more positive examples’ existence, and hence, are compatible with Popper’s falsification thought. (shrink)

The COVID-19 pandemic has helped to clarify the fair and equitable allocation of scarce medical resources, both within and among countries. The ethical allocation of such resources entails a three-step process: (1) elucidating the fundamental ethical values for allocation, (2) using these values to delineate priority tiers for scarce resources, and (3) implementing the prioritisation to faithfully realise the fundamental values. Myriad reports and assessments have elucidated five core substantive values for ethical allocation: maximising benefits and minimising harms, mitigating (...) unfair disadvantage, equal moral concern, reciprocity, and instrumental value. These values are universal. None of the values are sufficient alone, and their relative weight and application will vary by context. In addition, there are procedural principles such as transparency, engagement, and evidence-responsiveness. Prioritising instrumental value and minimising harms during the COVID-19 pandemic led to widespread agreement on priority tiers to include health-care workers, first responders, people living in congregate housing, and people with an increased risk of death, such as older adults and individuals with medical conditions. However, the pandemic also revealed problems with the implementation of these values and priority tiers, such as allocation on the basis of population rather than COVID-19 burden, and passive allocation that exacerbated disparities by requiring recipients to spend time booking and travelling to appointments. This ethical framework should be the starting point for the allocation of scarce medical resources in future pandemics and other public health conditions. For instance, allocation of the new malaria vaccine among sub-Saharan African countries should be based not on reciprocity to countries that participated in research, but on maximally reducing serious illness and deaths, especially among infants and children. (shrink)