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Introduction: The emergence of artificial intelligence (AI) chat programs has opened two distinct paths, one enhancing interaction and another potentially replacing personal understanding. Ethical and legal concerns arise due to the rapid development of these programs. This paper investigates academic discussions on AI in medicine, analyzing the context, frequency, and reasons behind these conversations. Methods: The study collected data from the Web of Science database on articles containing the keyword "ChatGPT" published from January to September 2023, resulting in 786 medically related journal articles. The inclusion criteria were peer-reviewed articles in English related to medicine. Results: The United States led in publications (38.1%), followed by India (15.5%) and China (7.0%). Keywords such as "patient" (16.7%), "research" (12%), and "performance" (10.6%) were prevalent. The Cureus Journal of Medical Science (11.8%) had the most publications, followed by the Annals of Biomedical Engineering (8.3%). August 2023 had the highest number of publications (29.3%), with significant growth between February to March and April to May. Medical General Internal (21.0%) was the most common category, followed by Surgery (15.4%) and Radiology (7.9%). Discussion: The prominence of India in ChatGPT research, despite lower research funding, indicates the platform's popularity and highlights the importance of monitoring its use for potential medical misinformation. China's interest in ChatGPT research suggests a focus on Natural Language Processing (NLP) AI applications, despite public bans on the platform. Cureus' success in publishing ChatGPT articles can be attributed to its open-access, rapid publication model. The study identifies research trends in plastic surgery, radiology, and obstetric gynecology, emphasizing the need for ethical considerations and reliability assessments in the application of ChatGPT in medical practice. Conclusion: ChatGPT's presence in medical literature is growing rapidly across various specialties, but concerns related to safety, privacy, and accuracy persist. More research is needed to assess its suitability for patient care and implications for non-medical use. Skepticism and thorough review of research are essential, as current studies may face retraction as more information emerges. [ABSTRACT FROM AUTHOR]

Objective: This paper offers a mini-review of OpenAI's language model, ChatGPT, detailing its mechanisms, applications in healthcare, and comparisons with other large language models (LLMs). Methods: The underlying technology of ChatGPT is outlined, focusing on its neural network architecture, training process, and the role of key elements such as input embedding, encoder, decoder, attention mechanism, and output projection. The advancements in GPT-4, including its capacity for internet connection and the integration of plugins for enhanced functionality are discussed. Results: ChatGPT can generate creative, coherent, and contextually relevant sentences, making it a valuable tool in healthcare for patient engagement, medical education, and clinical decision support. Yet, like other LLMs, it has limitations, including a lack of common sense knowledge, a propensity for hallucination of facts, a restricted context window, and potential privacy concerns. Conclusion: Despite the limitations, LLMs like ChatGPT offer transformative possibilities for healthcare. With ongoing research in model interpretability, common-sense reasoning, and handling of longer context windows, their potential is vast. It is crucial for healthcare professionals to remain informed about these technologies and consider their ethical integration into practice. [ABSTRACT FROM AUTHOR]

In 2021, a large urban university-based hospital transitioned to a new two-floor emergency department. Despite the new environment, there were usability and workflow challenges with the space. The authors of this paper created a multidisciplinary, human-centered design collaborative of clinicians, university faculty, and students in an effort to increase emergency department efficiency. After thorough design-research and clinician-focused collaboration, the authors and design team identified the need to improve medical supply retrieval time, which directly impacts patient care and clinician satisfaction. The primary interventions consisted of a redesign that is as follows: (a) created standardized icons related to organ system, (b) increased visibility of supply labels, and (c) reorganized supplies based on usage data. Although a successful project, it was not without several barriers discussed in this article, including design researcher and clinician-level setting and engagement, academic/institutional policies, and conflicting schedules. In addition, the lessons learned from implementing human-centered design concepts into clinical workflow sets forth future research opportunities and inspiration for other institutions to collaborate. [ABSTRACT FROM AUTHOR]

Despite decades of policies to widen participation in medical degrees, students selected for Medicine continue to reflect a socially elite group, rather than the diversity of the communities that graduates will serve. While research has documented experiences of students from disadvantaged backgrounds, this paper examines the "cultures of success" that enable advantaged students to gain entry to medical school. It documents how these students' school and home environments enable the development and realisation of "aspirational capacity". Aspirational capacity is not just about having a dream, but also the resources and knowledge to realise one's dream. The paper also examines a negative side of a narrow aspirational focus. "Aspirational constriction" describes the premature foreclosure of career ambitions, which can have negative implications for both the students and for society, and for less advantaged students, who are effectively excluded from degrees such as Medicine. [ABSTRACT FROM AUTHOR]

This paper aims to highlight the potential applications and limits of a large language model (LLM) in healthcare. ChatGPT is a recently developed LLM that was trained on a massive dataset of text for dialogue with users. Although AI-based language models like ChatGPT have demonstrated impressive capabilities, it is uncertain how well they will perform in real-world scenarios, particularly in fields such as medicine where high-level and complex thinking is necessary. Furthermore, while the use of ChatGPT in writing scientific articles and other scientific outputs may have potential benefits, important ethical concerns must also be addressed. Consequently, we investigated the feasibility of ChatGPT in clinical and research scenarios: (1) support of the clinical practice, (2) scientific production, (3) misuse in medicine and research, and (4) reasoning about public health topics. Results indicated that it is important to recognize and promote education on the appropriate use and potential pitfalls of AI-based LLMs in medicine. [ABSTRACT FROM AUTHOR]

In this paper, we describe a review concerning the Quantum Computing (QC) and Deep Learning (DL) areas and their applications in Computational Intelligence (CI). Quantum algorithms (QAs), engage the rules of quantum mechanics to solve problems using quantum information, where the quantum information is concerning the state of a quantum system, which can be manipulated using quantum information algorithms and other processing techniques. Nowadays, many QAs have been proposed, whose general conclusion is that using the effects of quantum mechanics results in a significant speedup (exponential, polynomial, super polynomial) over the traditional algorithms. This implies that some complex problems currently intractable with traditional algorithms can be solved with QA. On the other hand, DL algorithms offer what is known as machine learning techniques. DL is concerned with teaching a computer to filter inputs through layers to learn how to predict and classify information. Observations can be in the form of plain text, images, or sound. The inspiration for deep learning is the way that the human brain filters information. Therefore, in this research, we analyzed these two areas to observe the most relevant works and applications developed by the researchers in the world. [ABSTRACT FROM AUTHOR]

Background and Objective: Precision medicine highlights the importance of exploring heterogeneity in the effectiveness and costs of interventions. Our objective was to identify and compare frameworks for valuing heterogeneity-informed decisions, and consider their strengths and weaknesses for application to precision medicine.Methods: We conducted a scoping review to identify papers that proposed an analytical framework to place a value, in terms of costs and health benefits, on using heterogeneity to inform treatment selection. The search included English-language papers indexed in MEDLINE, Embase or EconLit, and a manual review of references and citations. We compared the frameworks qualitatively considering: the purpose and setting of the analysis; the types of precision medicine interventions where the framework could be applied; and the framework's ability to address the methodological challenges of evaluating precision medicine.Results: Four analytical frameworks were identified: value of stratification, value of heterogeneity, expected value of individualised care and loss with respect to efficient diffusion. Each framework is suited to slightly different settings and research questions. All focus on maximising net benefit, and quantify the opportunity cost of ignoring heterogeneity by comparing individualised or stratified decisions to a means-based population-wide decision. Where the frameworks differ is in their approaches to uncertainty, and in the additional metrics they consider.Conclusions: Identifying and utilising heterogeneity is at the core of precision medicine, and the ability to quantify the value of heterogeneity-informed decisions is critical. Using an analytical framework to value heterogeneity will help provide evidence to inform investment in precision medicine interventions, appropriately capturing the value of targeted health interventions. [ABSTRACT FROM AUTHOR]

In India, where there is no centralized medical records system, biomedical care providers rely on families to explain their child's illness and to carry records of any previous treatment the child may have received. Drawing on discussions of documentation, I argue that in the context of medical treatment for pediatric seizures, (1) families collect medical records to enable and shape their child's medical treatment, and (2) such a merging of medical and familial care is necessitated by the nature of their child's illness and the structure of the Indian healthcare system. Based on ethnographic fieldwork in Meerut and New Delhi, this paper attends to practices of record keeping to understand the demands biomedical institutions place on families for the treatment of their child's seizures. I examine the creation, maintenance, and movement of medical records to suggest that documents are a point of intersection between medical and kinship practices. They are artifacts of care that can narrate parallel histories of a patient's illness and family-clinician efforts to alleviate a child's suffering. [ABSTRACT FROM AUTHOR]

Background: Outcomes-based agreements (OBAs) have the potential to provide more timely patient access to novel therapies, although they are not suitable for every new medication or reimbursement scenario. The authors of this paper studied how to operationalize an OBA in oncology by leveraging existing real-world data (RWD) infrastructure in the province of Alberta. Objective: The main objectives were to (1) evaluate which health outcomes in oncology are suitable for OBAs and whether they can be tracked with existing infrastructure, and (2) determine how RWD in oncology can be used to implement an OBA and the expected timing for delivery. Methods: Using the Oncology Outcomes (O2) Group infrastructure and Alberta administrative data, a review of five key oncology outcomes was performed to determine suitability to support an OBA. Results: Overall survival and time-to-next-treatment were determined as potentially suitable oncology outcomes for OBAs; progression-free survival, patient-reported outcomes, and return to work were deemed inadequate for OBAs at the current time due to data limitations. Conclusions: Results indicate that it is feasible to leverage RWD to support OBAs in oncology in Alberta, with minimal additional data, resources, and infrastructure. The operational processes and steps to collect and analyze RWD for OBAs were identified, starting with performing an RWD feasibility study. The expected timeframe to fulfill the real-world evidence (RWE) requirements for an OBA is approximately 3 years for cancers with short trajectories. [ABSTRACT FROM AUTHOR]

The religious context of death has deep implications in shaping the phenomenon of death for the denizens of Kashi. The present paper argues that religious understanding of death confronts the medical issue(s) in the contemporary scenario. To explore the abysmal religio-cultural underpinning(s) of the episteme of death and dying in the era of hegemonic medical technologies is the purpose of this study. Further, it will discuss the enigma of death and dying and will represent some insights into it from the vantage point of religion. [ABSTRACT FROM AUTHOR]

Hyperhidrosis is a dermatosis presenting as pathologically excessive focal or generalized sweating. The stigmatizing nature of hyperhidrosis may cause patients to feel embarrassment and apprehension about their symptoms and experience a significant decrease in well-being. Severe cases of hyperhidrosis can also increase the risk of developing psychiatric and somatic comorbidities. Conventional non-surgical treatments of hyperhidrosis include aluminum salts, iontophoresis, botulinum toxin injections, and oral glycopyrronium. In recent years, new topical anticholinergic medications and devices have emerged that may improve the patients' symptoms and even prevent the development of comorbidities. The treatment of hyperhidrosis can be a complex matter and may require the combination of several therapies. The purpose of this paper was to firstly review the literature on existing non-surgical treatment options for hyperhidrosis, and secondly provide a stepwise approach to investigating and treating patients with hyperhidrosis. [ABSTRACT FROM AUTHOR]

The definitions and conceptualizations of health, and the management of healthcare have been challenged by the current global scenarios (e.g., new diseases, new geographical distribution of diseases, effects of climate change on health, etc.) and by the ongoing scholarship in humanities and science. In this paper we question the mainstream definition of health adopted by the WHO—‘a state of complete physical, mental and social well-being and not merely the absence of disease or infirmity’ (WHO in Preamble to the constitution of the World Health Organization as adopted by the international health conference, The World Health Organization, 1948)—and its role in providing tools to understand what health is in the contemporary context. More specifically, we argue that this context requires to take into account the role of the environment both in medical theory and in the healthcare practice. To do so, we analyse WHO documents dated 1984 and 1986 which define health as ‘coping with the environment’. We develop the idea of ‘coping with the environment’, by focusing on two cardinal concepts: adaptation in public health and adaptivity in philosophy of biology. We argue that the notions of adaptation and adaptivity can be of major benefit for the characterization of health, and have practical implications. We explore some of these implications by discussing two recent case studies of adaptivity in public health, which can be valuable to further develop adaptive strategies in the current pandemic scenario: community-centred care and microbiologically healthier buildings. [ABSTRACT FROM AUTHOR]

In the paper "An archeology of corruption in medicine" (2018), Miles Little, Wendy Lipworth, and Ian Kerridge ("the authors" or "Little et al.") present an account of corruption and describe its prevalent forms in medicine. In presenting an individual-focused account of corruption found within "social entities" (organizations, institutions, and systems), Little et al. argue that these entities are corruptible by nature and that certain individuals are prone to take advantage of the corruptibility of social entities to pursue their own ends. The authors state that this is not preventable, so the way to remedy corruption is via management and, where necessary, punishment. This commentary will briefly lay out the key features and functions of corruption as presented by Little et al., before providing a critical discussion that will focus on whether corruptibility is a necessary feature of social entities. I will propose that it is not a necessary feature, though it may frequently arise where individualistic values are unchecked. Corruption can be prevented within social entities by enhancing structures that direct toward virtue and which promote and reward cooperation instead of competition. [ABSTRACT FROM AUTHOR]

Species lists are widely used in legislation and regulation to manage and conserve biodiversity. In this paper, we explore the issues caused by the lack of an adequately governed and universally accepted list of the world's species. These include lack of quality control, duplicated effort, conflicts of interest, lack of currency, and confusion in the scientific use of taxonomic information. If species lists are to fulfill their role efficiently, then the governance systems underlying their creation must keep pace. Fortunately, modernization of species list governance is now possible as a result of advances in biodiversity informatics and two decades of experience working to create the backbone of a global species list. [ABSTRACT FROM AUTHOR]