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[Display omitted] • Sensitivity analysis in packaging EoL modeling to evaluate influence in EoL impacts. • Take-back presents environmental benefits due to paper and glass recycling. • Incineration with energy recovery reduces EoL impacts from pharmaceutical packaging. • Smaller pharmaceutical packaging and EoL valorization reduces impacts. • Decisions at packaging early design stage influence EoL impacts. Pharmaceutical packaging waste has increased due to a higher global demand for pharmaceutical products, leading to more waste generation and associated environmental impacts. The main goal of this article is to present a cradle-to-grave life cycle assessment of pharmaceutical packaging, evaluating end-of-life (EoL) alternatives, aiming to identify hotspots and opportunities for improvement. A life cycle model was implemented for three types of pharmaceutical packaging (blisters, sachets, bottles; 23 packaging). The functional unit is the storage and delivery of medicines containing the same active pharmaceutical ingredient, dosage, and amount of medicines. Two EoL analyses were performed: 1) compare take-back (recycling and incineration) with domestic waste collection (landfill or incineration); and 2) assess different EoL situations of pharmaceutical packaging in Europe. A life cycle impact assessment was performed for 13 categories. Analysis 1 shows that take-back presents lower environmental impacts than domestic waste collection for seven out of 13 categories due to paper and glass recycling benefits. Analysis 2 shows that in the take-back, higher amounts of packaging are recycled or incinerated, which leads to lower EoL impacts. A sensitivity analysis was performed to evaluate the influence of parameters and assumptions in packaging EoL impacts. Packaging production contributes significantly to life cycle impacts, followed by transportation, EoL, and packing process. Ecodesign initiatives are recommended, such as packaging with less material and volume, using materials with lower impacts to significantly reduce the impacts of pharmaceutical packaging. [ABSTRACT FROM AUTHOR]

The article presents the discussion on 2023 ANZCA Annual Scientific Meeting (ASM) was held on 5–9 May 2023 in Sydney, Australia.

This paper aims to interpret the role of the soul as ontological, intellectual or cognitive and as the moral principle within the frame of the holistic conception of human psychosomatic health that emerges from the context of Zalmoxian medicine in the proemium of Plato's Charmides. It examines what the ontological status of the soul is in relation to the body and the body–soul complex of man considered as a psychosomatic whole. By comparing the presentation of the soul as principle in the Charmides and the Phaedrus, the paper defends the thesis that in the former dialogue, Plato develops his own anthropological ontology, which paves the way for the salvation of human existence and health. The soul is bestowed with an ontological primacy that determines the philosophical and medical presuppositions for treating human illness under a holistic view. The interpretation of the ontological relation of the soul to the body and the entire human being in the context of Zalmoxian holistic medicine is based on Hermias Alexandrinus' exegesis of the conception of the soul as principle in the Phaedrus. This paper demonstrates that, from both the medical holistic viewpoint and the anthropological philosophical perspective, the soul is the principle and πρῶτον with regard to the body and the body–soul complex without being the whole that the corresponding medical epistemology must apprehend. [ABSTRACT FROM AUTHOR]

This introduction to a special section brings together three papers first presented at a panel, 'Medical Professions in South Asia: Historical and Contemporary Analyses', at the 26th European Conference on South Asian Studies, held in Vienna, Austria and online, in July 2021. All three papers deal with aspects of the professionalisation of biomedical doctors in India since its independence in 1947. The authors bring together historical and sociological approaches to illuminate the growth of specialisms, patterns of practitioner–patient interactions and efforts to maintain occupational closure and maintain status in the face of growing challenges. The introduction concludes with a discussion of the relevance of these papers for the sociology of health and illness in India and beyond. [ABSTRACT FROM AUTHOR]

The quality of the very early emotional experiences in a child's life are recognized today as foundational in the mental health of becoming an adult. Unsurprisingly, clinicians and health authorities agree on the importance of early detection and treatment of any mental health issues experienced by the preschool child. This is even more important and challenging as young children do not yet have the language skills necessary to express their distress. But do the caregivers in charge of these populations have the best tools at their disposal to carry out that important mission in an efficient and scientifically robust manner reflecting the latest research findings and scientific literature? This is the question we try to answer in this paper. We revisited the theoretical underpinnings behind the concept of mentalization as playing a key role in the ability to understand the other's inner reality. We then carried out an extensive review of scientific papers written over the past 30 years on the subject. We examined mental representations of the adult on the child and analyzed those mentalizations as key inputs. We focused on extracting cross analyses of the mentalizations of one child by several adults with different functions in the life of the child. In this process, we used the PRISMA methodology applied to large international medical databases. We found that the qualitative approach, usually associated with a lengthy process, has been overwhelmingly used in trying to assess patients' mental states and to analyze the mentalizations on the patient, adult or child. Furthermore, cross analyses of mentalizations from more than one adult on a given child were almost nonexistent, despite having high epistemic and clinical potential. There is a dearth of reliable quantitative tools, able to capture and analyze the mentalizations on a patient, that are scientifically robust, transposable, and easy to implement in a clinical setting. The absence of such tools for medical professionals in charge of assessing preschool children contributes, in our view, the low detection and poor treatment of mental disorders in that particularly vulnerable population. We believe there is here an urgent unmet need and that such tools should be designed, validated, and deployed into the target populations as early as possible. [ABSTRACT FROM AUTHOR]

As previous research has observed, medical students and physicians alike confront vast amounts of knowledge in their education and practice, such that no one clinician can know everything there is to know about biomedicine. Even before clerkships, medical students learn to cope with this impossibility by prioritizing certain information based on its perceived utility for exams and clinical practice. Many factors can shape this process, including teamwork, wherein individual medical students rely on one another to address gaps in knowledge at the level of the group. This paper will draw on qualitative data from two allopathic medical schools in the American Midwest to demonstrate that peer-to-peer learning, a widely utilized pedagogical modality in North American medical schools, is amongst the earliest places where future physicians learn how to rely on their peers in the profession as they make choices about what to know and what not to know about biomedicine: cultivating a culture of "intraprofessionalism" between students with different knowledges and values, as they prepare to enter the same profession. The paper will also consider how differences in the student populations at two field sites impact intraprofessional development. Drawing on scholarship of peer-based learning strategies and the sociology and anthropology of medical education, the authors argue that peer-to-peer learning is a key site in the professional socialization of medical students toward the effective management of medical knowledge. [ABSTRACT FROM AUTHOR]

This study presents and explains the phenomenon of indexjacking, which involves the systematic infiltration of hijacked journals into international indexing databases, with Scopus being one of the most infiltrated among these databases. Through an analysis of known lists of hijacked journals, the study identified at least 67 hijacked journals that have penetrated Scopus since 2013. Of these, 33 journals indexed unauthorized content in Scopus and 23 compromised the homepage link in the journal's profile, while 11 did both. As of September 2023, 41 hijacked journals are still compromising the data of legitimate journals in Scopus. The presence of hijacked journals in Scopus is a challenge for scientific integrity due to the legitimization of unreliable papers that have not undergone peer review and compromises the quality of the Scopus database. The presence of hijacked journals in Scopus has far‐reaching effects. Papers published in these journals may be cited, and unauthorized content from these journals in Scopus is thus imported into other databases, including ORCID and the WHO COVID‐19 Research Database. This poses a particular challenge for research evaluation in those countries, where cloned versions of approved journals may be used to acquire publications and verifying their authenticity can be difficult. [ABSTRACT FROM AUTHOR]

This paper introduces Mahāyāna Buddhist medicine into the contemporary international relations (IR) literature. In this paper, we will elucidate the perception towards subjectivity and relationality based upon the non-binary relationality of Mahāyāna Buddhist medicine, and strive to provide a refreshing understanding of the world. In order to achieve this goal, we start this article by focussing upon the way in which the essentialised subjectivity became the norm of contemporary IR even in non-Western regions. Second, we will provide a general introduction to Mahāyāna Buddhism. Here, we will explain the fluid subjectivity of this particular philosophical tradition, particularly its assumptions of subjectivity, relationality and temporality. Third, we will shift our focus to a practical application of this line of thought, Mahāyāna Buddhist medicine. We argue that Mahāyāna Buddhist medicine is extremely suggestive to contemporary colonial/postcolonial relations in the sense that it provides a practical way to cure those who are suffering from fear and anxiety generated by the assumptions of autonomy and independence. Last, we will return to the discourses of IR, in particular a recent discussion on temporality, relationality and ethics, to consider the possible contributions of Mahāyāna Buddhist medicine to IR. [ABSTRACT FROM AUTHOR]

Background: Daith piercing is a special ear‐piercing method that punctures the crus of the helix. The penetrated site at the ear's innermost point is assumed to stimulate a pressure point associated with the vagus nerve. It has been reported that the pierced spot relieves migraine and tension‐type headaches by activating vagal afferents, leading to the inhibition of neurons in the caudal trigeminal nucleus via the nucleus tractus solitarii. Objective: The objective of this narrative literature review is to summarize the current state of knowledge concerning daith piercing for the treatment of migraine and tension‐type headaches from the perspectives of the Chinese and Western auricular systems. Methods: PubMed and China National Knowledge Infrastructure databases were searched using the keywords "daith piercing," "auricular points," "headache," and "acupuncture" from database inception to September 1, 2023. Only studies on humans were eligible; otherwise, no further restrictions were applied to the study designs, type of headache, or patient population of the identified articles. Bibliographies of all eligible studies were screened for further eligible studies. The main outcome of interest was a quantitative measure of pain relief by daith piercing. Secondary outcomes were relapse time of headache and further outcomes related to daith piercing, if available. Results: From a total of 186 identified articles, one retrospective study and three case reports fulfilled the inclusion criteria. No clinical trial was identified. The obtained studies describe patients experiencing chronic headaches undergoing daith piercing without changing or reducing their usual medication. In all case studies and the retrospective study, patients reported substantial reductions in pain immediately after daith piercing; however, headache symptoms recurred several weeks to months thereafter. From the perspective of the Chinese and Western auricular systems, no sufficient explanation for the described treatment effect of daith piercing was found. Conclusion: The available literature, combined with the reported recurrence of pain as well as the associated side effects of daith piercing, indicate that current evidence does not support daith piercing for the treatment of migraine, tension‐type headaches, or other headache disorders. Plain Language Summary: This paper summarizes what we know about Daith piercing (DP) for chronic migraine and tension‐type headache and discusses how DP might work. Current evidence does not support DP as an effective treatment of chronic migraine and tension‐type headache. These findings might assist clinicians in discussing this subject with patients as well as guide future research. Plain Language Summary: This paper summarizes what we know about Daith piercing (DP) for migraine and tension‐type headache and discusses how DP might work. Current evidence does not support DP as an effective treatment of migraine and tension‐type headache. These findings might assist clinicians in discussing this subject with patients as well as guide future research. [ABSTRACT FROM AUTHOR]

This paper focuses on a specific aspect of the emergence of psychology and psychiatry as scientific disciplines in the late eighteenth and early nineteenth centuries. It examines how psychological knowledge, which was scattered across different fields of knowledge such as philosophy and anthropology, as well as medical subfields such as physiology, pathology and state medicine, was filtered into medical education in three medical faculties of the Habsburg Monarchy: Vienna, Prague and Pest. As education was the primary arena of producing authoritative medical knowledge, the three institutions played a key role in the transfers of knowledge within the Monarchy and in shaping 'official' medical practices acknowledged by the state. These in turn could be used to validate different measures to normalize or optimize its population. Through the lens of education and the underlying tension between the different approaches to psychological knowledge that constituted a type of 'arcane knowledge' in the period, with fluid and often dubious boundaries and questionable applicability, the article points at the epistemological uncertainty and transitory nature of the psychological field. The paper also looks at how it was nevertheless integrated into medical education with varying success by the 1840s as part of the professionalization of psychiatry and with the pronounced aim of training specialists who could cooperate in creating functioning spaces for the mad where they could not only be kept, but also normalized and (re)integrated into society. [ABSTRACT FROM AUTHOR]

Emerging research points to the increasingly expansive ontologies of gender that young people engage with in contemporary society. This paper examines the representations of gender that emerged in one urban site: a science gallery exhibition in London that sought to de-centre fixed binary gender categories – a site where gender is explicitly being 'redone' (West & Zimmerman, 2009). Drawing on research work on curation (Acord, 2010) we examine data (drawings and text) produced by 516 young people who attended the exhibition, exploring the ways gender is narrativised and re-curated within the physical and discursive space(s) of the gallery. Our findings show the ways that gender was felt and represented in these recurations, as fixed and unfixed, and productive and unproductive. The participants reassembled the ideas of gender presented within the gallery through representations imbued with affect. This included representations that conflated sex and gender and privileged bio-essentialist narratives, as well as representations that drew on binary models and logics. These re-curations, we argue, point to the ways that young people are making sense of gender (im)possibilities. We argue that these narratives highlight the ways young people are grappling with discourses of gender as they transition into adulthood in contemporary society. [ABSTRACT FROM AUTHOR]

Introduction: Stem cells from human exfoliated deciduous teeth (SHED) are currently receiving much attention because SHED has the potential to be widely used in regenerative medicine. The lineage-specific differentiation tendency of SHED, especially endothelial and neural differentiation, could be beneficial as neural innervation and blood vessel formation are essential in tissue regeneration. Streptococcus mutans (S. mutans) is the major bacterial cause of dental caries. At the same time, Staphylococcus aureus (S. aureus) is the bacterial cause of oral infections such as cheilitis, osteomyelitis, stomatitis, gingivitis, and dentoalveolar abscess. α-mangostin can inhibit bacterial growth by disrupting the cytoplasmic membrane of the bacteria. Epigallocatechin-3-gallate (EGCG) has a powerful antibacterial function, especially against gram-positive bacteria such as S. mutans and S. aureus. This study aimed to prove the inhibitory effect of SHED metabolite in combination with α-mangosteen and EGCG against S. aureus and S. mutans bacteria. Materials and methods: The study isolated and characterized metabolites from SHED in a specific medium. Subsequently, the combination of metabolites with α-mangostin and EGCG was made in a 1:1 ratio. The bacterial inhibition zones were measured on disk paper placed on bacterial growth media. Results: The combination of SHED metabolites with α-mangostin and EGCG significantly inhibited the growth of S. aureus and S. mutans bacteria. Conclusion: Combining SHED metabolites with α-mangostin and EGCG exhibits antibacterial properties against S. aureus and S. mutans bacteria. The combination of SHED metabolites with α-mangostin has higher inhibition results than the combination of SHED metabolites with EGCG. [ABSTRACT FROM AUTHOR]

Background/Objectives: Temporomandibular disorder (TMD) is the term used to describe a pathology (dysfunction and pain) in the masticatory muscles and temporomandibular joint (TMJ). There is an apparent upward trend in the publication of dental research and a need to continually improve the quality of research. Therefore, this study was conducted to analyse the use of sample size and effect size calculations in a TMD randomised controlled trial. Methods: The period was restricted to the full 5 years, i.e., papers published in 2019, 2020, 2021, 2022, and 2023. The filter article type—"Randomized Controlled Trial" was used. The studies were graded on a two-level scale: 0–1. In the case of 1, sample size (SS) and effect size (ES) were calculated. Results: In the entire study sample, SS was used in 58% of studies, while ES was used in 15% of studies. Conclusions: Quality should improve as research increases. One factor that influences quality is the level of statistics. SS and ES calculations provide a basis for understanding the results obtained by the authors. Access to formulas, online calculators and software facilitates these analyses. High-quality trials provide a solid foundation for medical progress, fostering the development of personalized therapies that provide more precise and effective treatment and increase patients' chances of recovery. Improving the quality of TMD research, and medical research in general, helps to increase public confidence in medical advances and raises the standard of patient care. [ABSTRACT FROM AUTHOR]

We present in this paper some of the existing machine learning and sound processing techniques involved in the medical process and show how they can be applied in the context of a vocal disease detection task. The machine learning techniques are the usual, ranging from decision trees to neural networks, and when it comes to the sound processing approaches some scientists probably are familiar with them from the speech processing or music analysis areas. However, the techniques are adapted to the particularities of the medical field - data collection, verification, etc. Through the concrete example of the vocal disease detection task we worked on, we made some interesting observations, both on the classification ability of the model and on the influence of the data. [ABSTRACT FROM AUTHOR]

Physicians generally recommend that patients resuscitated with naloxone after opioid overdose stay in the emergency department for a period of observation in order to prevent harm from delayed sequelae of opioid toxicity. Patients frequently refuse this period of observation despiteenefit to risk. Healthcare providers are thus confronted with the challenge of how best to protect the patient's interests while also respecting autonomy, including assessing whether the patient is making an autonomous choice to refuse care. Previous studies have shown that physicians have widely divergent approaches to navigating these conflicts. This paper reviews what is known about the effects of opioid use disorder on decision-making, and argues that some subset of these refusals are non-autonomous choices, even when patients appear to have decision making capacity. This conclusion has several implications for how physicians assess and respond to patients refusing medical recommendations after naloxone resuscitation. [ABSTRACT FROM AUTHOR]

Neuro-fuzzy techniques have been widely used in many applications due to their ability to generate interpretable fuzzy rules. Ensemble learning, on the other hand, is an emerging paradigm in artificial intelligence used to improve performance results by combining multiple single learners. This paper aims to develop and evaluate a set of homogeneous ensembles over four medical datasets using hyperparameter tuning of four neuro-fuzzy systems: adaptive neuro-fuzzy inference system (ANFIS), Dynamic evolving neuro-fuzzy system (DENFIS), Hybrid fuzzy inference system (HyFIS), and neuro-fuzzy classifier (NEFCLASS). To address the interpretability challenges and to reduce the complexity of high-dimensional data, the information gain filter was used to identify the most relevant features. After that, the performance of the neuro-fuzzy single learners and ensembles was evaluated using four performance metrics: accuracy, precision, recall, and f1 score. To decide which single learners/ensembles perform better, the Scott-Knott and Borda count techniques were used. The Scott-Knott first groups the models based on the accuracy to find the classifiers appearing in the best cluster, while the Borda count ranks the models based on all the four performance metrics without favoring any of the metrics. Results showed that: (1) The number of the combined single learners positively impacts the performance of the ensembles, (2) Single neuro-fuzzy classifiers demonstrate better or similar performance to the ensembles, but the ensembles still provide better stability of predictions, and (3) Among the ensembles of different models, ANFIS provided the best ensemble results. [ABSTRACT FROM AUTHOR]

The objective of the ASPIRE award programme of the International Association for Health Professions Education is to go beyond traditional accreditation processes. Working in partnership with the ASPIRE Academy, the programme aims to encourage and support excellence in health professions education, in part by showcasing and exemplifying best practices. Each year ASPIRE award applications received from institutions across the globe describe their greatest achievements in a variety of areas, one of which is curriculum development, where evaluation of applications is carried out using a framework of six domains. These are described in this paper as key elements of excellence, specifically, Organisational Structure and Curriculum Management; Underlying Educational Strategy; Content Specification and Pedagogy; Teaching and Learning Methods and Environment; Assessment, Monitoring and Evaluation; Scholarship. Using examples from the content of submissions of three medical schools from very different settings that have been successful in the past few years, achievements in education processes and outcomes of institutions around the world are highlighted in ways that are relevant to their local and societal contexts. [ABSTRACT FROM AUTHOR]

Current attempts to understand unusually high rates of psychiatric illness in complex, chronic illnesses can be guilty of operating within an explanatory framework whereby there are two options. Either (a) that the psychiatric predicaments are secondary to the bodily condition, and (b) that they are primary. In this paper, I draw upon philosophical work on affect, contemporary empirical work, and qualitative first-person patient data to illustrate a much messier reality. I argue that affective experience is generally more complex in such conditions, and that a variety of pre- and post-morbid causal factors dynamically interact such that the resultant psychiatric predicaments do not permit to classification as strictly primary or secondary to the bodily condition. Affective scaffolding, in my view, provides an apt theoretical framework for capturing this nuance. [ABSTRACT FROM AUTHOR]

Background: Patient handover (handoff in America) is the transfer of information and accountability among nurses assigned to patient care. Introduction, Situation, Background, Assessment, and Recommendation (ISBAR) is currently the most popular framework for framing handovers. However, research shows that incomplete handovers and information transfers among healthcare providers and nurses exist and are responsible for adverse patient events. Materials and Methods: The current systematic review aims to view contemporary literature on handover, especially but not exclusively in psychiatric settings, and to extract current conditions from Electronic Patient Records (EPRs) using the ISBAR framework. A total of fifty-five scientific papers were selected to support the scoping review. Eligibility criteria included structured research to analyze outcomes, completed by reviewing policy papers and professional organization guidelines on I/SBAR handovers. Results: Our systematic review shows that the application of ISBAR increases interprofessional communication skills and confidence and the quality of the transfer of clinical information about patients, resulting in increased patient safety and quality of care. Conclusions: Implementing the knowledge and application of structured patient handover will respond to current recommendations for service improvement and quality of care. Furthermore, nurses who use ISBAR also reported its benefits as they feel they can deliver what is required for patient care information in a structured, fast, and efficient way. A further increase in the efficacy of handovers is reported by using EPR. [ABSTRACT FROM AUTHOR]

In 2022, the Camden Coalition Medical-Legal Partnership began providing civil and criminal legal services to substance use disorder patients at Cooper University Health Care's Center for Healing. This paper discusses early findings from the program's first year on the efficacy of the provision of criminal-legal representation, which is uncommon among MLPs and critical for this patient population. The paper concludes with takeaways for other programs providing legal services in an addiction medicine setting. [ABSTRACT FROM AUTHOR]

AbstractA novel advantage of the use of machine learning (ML) systems in medicine is their potential to continue learning from new data after implementation in clinical practice. To date, considerations of the ethical questions raised by the design and use of adaptive machine learning systems in medicine have, for the most part, been confined to discussion of the so-called “update problem,” which concerns how regulators should approach systems whose performance and parameters continue to change even after they have received regulatory approval. In this paper, we draw attention to a prior ethical question: whether the continuous learning that will occur in such systems after their initial deployment should be classified, and regulated, as medical research? We argue that there is a strong prima facie case that the use of continuous learning in medical ML systems should be categorized, and regulated, as research and that individuals whose treatment involves such systems should be treated as research subjects. [ABSTRACT FROM AUTHOR]

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]

This paper explores physicians' responses to the suicide of a female surgeon colleague in order to detail the cultural patterning of the problem of suicide within biomedicine. More broadly, it argues that suicide provides an exemplary case of reckoning with uncertainty. Data sources include 124 hours of person-centered and semistructured interviews with 65 individuals, including 54 physicians, 28 of whom are female surgeons. I argue that the cultural model of suicide articulated by physicians reflects an ultimately ineffective strategy for managing suicide's multisource uncertainty, with the suicide of a colleague exposing the moral and affective entailments of a limit case of prognostication. Examining patterns in physician responses to suicide, I define "bewilderment" as a state of having no means of getting to know, and I detail the ways in which physicians' aversive reaction to bewilderment undermine knowledge acquisition. I describe suicide's distinct challenges to biomedicine's social power, including suicide's contestation of narratives about the future. Finally, I raise questions about the degree to which biomedical framings of suicide may undermine the ability of biomedical actors to develop effective interventions to address it. Exploring responses to suicide as a form of cultural production can illustrate fundamental tensions about uncertainty and causality. [ABSTRACT FROM AUTHOR]

OBJECTIVE: We, therefore, aim to conduct a systematic review to assess the academic potential of ChatGPT-3.5, along with its strengths and limitations when giving medical exams. METHOD: Following PRISMA guidelines, a systemic search of the literature was performed using electronic databases PUBMED/MEDLINE, Google Scholar, and Cochrane. Articles from their inception till April 4, 2023, were queried. A formal narrative analysis was conducted by systematically arranging similarities and differences between individual findings together. RESULTS: After rigorous screening, 12 articles underwent this review. All the selected papers assessed the academic performance of ChatGPT-3.5. One study compared the performance of ChatGPT-3.5 with the performance of ChatGPT-4 when giving a medical exam. Overall, ChatGPT performed well in 4 tests, averaged in 4 tests, and performed badly in 4 tests. ChatGPT's performance was directly proportional to the level of the questions' difficulty but was unremarkable on whether the questions were binary, descriptive, or MCQ-based. ChatGPT's explanation, reasoning, memory, and accuracy were remarkably good, whereas it failed to understand image-based questions, and lacked insight and critical thinking. CONCLUSION: ChatGPT-3.5 performed satisfactorily in the exams it took as an examinee. However, there is a need for future related studies to fully explore the potential of ChatGPT in medical education. [ABSTRACT FROM AUTHOR]

The evaluation of teaching can be an essential driver for curriculum development. Instruments for teaching evaluation are not only used for the purpose of quality assurance but also in the context of medical education research. Therefore, they must meet the common requirements for reliability and validity. This position paper from the GMA Teaching Evaluation Committee discusses strategic and methodological aspects of evaluation in the context of undergraduate medical education and related courses; and formulates recommendations for the further development of evaluation. First, a four-step approach to the design and implementation of evaluations is presented, then methodological and practical aspects are discussed in more detail. The focus here is on target and confounding variables, survey instruments as well as aspects of implementation and data protection. Finally, possible consequences from evaluation data for the four dimensions of teaching quality (structural and procedural aspects, teachers and outcomes) are discussed. [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 this paper, I will argue how Paracelsus's concept of the universal ensoulment of nature may relate to his understanding of the self-healing capacity of the body, as shown in his Grosse Wundartzney (1536). Here, his new approach to medicine is visible, focusing not on retaining or restoring the balance of bodily humours but on strengthening the inner "essence" of life (the so-called "balsam," "mummy," "astral spirit," etc.). This is possible by means of life-endowed essences of healing substances which can affect the body's vital principle by means of inner sympathies. Here, a link is established to medical alchemy as a way to produce more subtle medicines, the "essences" of things. Such an undertaking is possible only in the framework of the natural magic concept with its underlying microcosm-macrocosm analogy. It is my aim to show not only the principles of Paracelsus's new medicine, alchemy, and his worldview in general, but also how his theories may relate to his predecessors, including Marsilio Ficino, one of the few authors who escaped Paracelsus's harsh critique. [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]

Purpose: The present article summarises the characteristics of Rasch's theory, providing an original metrological model for persons' measurements. Properties describing the person "as a whole" are key outcome variables in Medicine. This is particularly true in Physical and Rehabilitation Medicine, targeting the person's interaction with the outer world. Such variables include independence, pain, fatigue, balance, and the like. These variables can only be observed through behaviours of various complexity, deemed representative of a given "latent" person's property. So how to infer its "quantity"? Usually, behaviours (items) are scored ordinally, and their "raw" scores are summed across item lists (questionnaires). The limits and flaws of scores (i.e., multidimensionality, non-linearity) are well known, yet they still dominate the measurement in Medicine. Conclusions: Through Rasch's theory and statistical analysis, scores are transformed and tested for their capacity to respect fundamental measurement axioms. Rasch analysis returns the linear measure of the person's property ("ability") and the item's calibrations ("difficulty"), concealed by the raw scores. The difference between a person's ability and item difficulty determines the probability that a "pass" response is observed. The discrepancy between observed scores and the ideal measures (i.e., the residual) invites diagnostic reasoning. In a companion article, advanced applications of Rasch modelling are illustrated. Questionnaires' ordinal scores are poor approximations of measures. The Rasch analysis turns questionnaires' scores into interval measures, provided that its assumptions are respected. Thanks to the Rasch analysis, accurate measures of independence, pain, fatigue, cognitive capacities and other whole person's variables of paramount importance in rehabilitation are available. The current work is addressed to rehabilitation professionals looking for an introduction to interpreting published results based on Rasch analysis. The first of a series of two, the present article illustrates the most common graphic and numeric outputs found in published papers presenting the Rasch analysis of questionnaires. [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]

Artificial intelligence (AI) is becoming increasingly important, especially in the medical field. While AI has been used in medicine for some time, its growth in the last decade is remarkable. Specifically, machine learning (ML) and deep learning (DL) techniques in medicine have been increasingly adopted due to the growing abundance of health-related data, the improved suitability of such techniques for managing large datasets, and more computational power. ML and DL methodologies are fostering the development of new "intelligent" tools and expert systems to process data, to automatize human–machine interactions, and to deliver advanced predictive systems that are changing every aspect of the scientific research, industry, and society. The Italian scientific community was instrumental in advancing this research area. This article aims to conduct a comprehensive investigation of the ML and DL methodologies and applications used in medicine by the Italian research community in the last five years. To this end, we selected all the papers published in the last five years with at least one of the authors affiliated to an Italian institution that in the title, in the abstract, or in the keywords present the terms "machine learning" or "deep learning" and reference a medical area. We focused our research on journal papers under the hypothesis that Italian researchers prefer to present novel but well-established research in scientific journals. We then analyzed the selected papers considering different dimensions, including the medical topic, the type of data, the pre-processing methods, the learning methods, and the evaluation methods. As a final outcome, a comprehensive overview of the Italian research landscape is given, highlighting how the community has increasingly worked on a very heterogeneous range of medical problems. [ABSTRACT FROM AUTHOR]

A correction is presented to the article "ANZCA Annual Scientific Meeting (ASM) Faculty of Pain Medicine (FPM) Best Free Paper Award Session Abstracts" published in November 29, 2022 issue.

The importance of grey literature as a means of primary, nonconventional communication is accepted in almost every scientific field. Although grey literature covers a wide spectrum of nonconventional documents, both producers and users of grey literature have always considered it to be a primary source of information. The National Library and Archives of Iran (NLAI) was founded in 1937. The main goal of this organization is collecting, preserving, organizing and disseminating information about printed and non-printed works in Iran, and taking measures and making decisions to guarantee the accuracy, ease and speed of research and study in all fields to promote national culture. In order to achieve these goals, and according to the law, all private and public publishers have to deposit a copy of their publications (book and non -book materials) to the NLAI. There are more than 1.790.000 issues in the grey literature in the NLAI, and over 170.000 of them belong to the Medicine group. In this study, the amount of grey resources in the field of medicine, nursing, dentistry, veterinary, paramedical and pharmacology in the NLAI is surveyed. How many grey literatures are there in each medical subject's groups? How many of them have been digitized? How many articles are in the field of medicine group? How many of them are conference papers? [ABSTRACT FROM AUTHOR]

By focusing on the concept of 'complexion' in the major medieval Latin commentaries on Aristotle's so-called De animalibus , this paper identifies and analyzes a case of the use of the concept of 'complexion' outside the medical context or, more precisely, at the intersection of natural philosophy and medicine. The preliminary survey undertaken in this paper suggests that 'complexion' was a key concept of the De animalibus tradition, i.e., the principle used to explain, in a unified manner, the issues at stake in the medieval scientia de animalibus. The paper further reflects on the reasons why the notion of 'complexion' could have served as an organizational principle of the themes treated in the De animalibus commentaries and on the role that the earliest medieval commentaries on the De animalibus themselves could have played in shaping some of the prominent features of the medieval conceptualization of 'complexion.' [ABSTRACT FROM AUTHOR]

According to Avicenna, the perfect (or complete) disposition (istiʿdād kāmil / tāmm) turns prime matter, which is potentially receptive to every form (or power, or quality), into complected matter, which is endowed with uniform quality. The latter, i.e., complexion (mizāǧ) or complexional form (ṣūra mizāǧiyya), is suitable to receive some particular form (or power, or quality) and not another. The question arises as to how matter acquires its specific complexion. Is it the result of celestial influence, or does it emerge from chemical, elemental interactions within matter? This paper tries to answer this question with textual evidence from Avicenna's natural philosophy and metaphysics. Together with soul/form, complected matter represents the other constituent of organic, living substances. The paper then attempts to determine which science is proper to its investigation. I argue that the investigation of organic matter, that is, the specific complexion characterizing the animal body (or its parts), pertains to zoology. Zoology is crucial to grounding medical practice, which operates on those specific complexions to preserve or restore health. [ABSTRACT FROM AUTHOR]

The Imperially Commissioned Golden Mirror of the Orthodox Lineage of Medicine (Yuzuan yizong jinjian 御纂醫宗金鑑), first printed in 1742, was one of the most important and widely circulating works on medicine in late imperial China. This paper analyzes a group of twenty-three medical manuscripts from the nineteenth and early twentieth century that include parts of the Golden Mirror. The findings suggest that most of the manuscripts should not be considered mere copies, but as deliberate selections. They served didactic as well as epistemic functions that differ from, or go beyond, those that could be fulfilled by the printed Golden Mirror (or a faithful manuscript copy alone). This is indicated not only by different content type selections (verse form for memorization or recitation; prose form for study or consultation) and the combination with medical knowledge from other sources, but also by the ways in which these contents were formatted, usually to facilitate reading and navigation. Adjustment, updating or supplementation of Golden Mirror contents likewise functioned epistemically, integrating previous medical knowledge into the medical discourse of the time. Hence, the findings of the present study help to clarify the lasting importance of manuscripts in the age of print, for which possibilities of adapting knowledge to personal interests and requirements seem to have been decisive factors. [ABSTRACT FROM AUTHOR]

Current national and international guidelines for the ethical design and development of artificial intelligence (AI) and robotics emphasize ethical theory. Various governing and advisory bodies have generated sets of broad ethical principles, which institutional decisionmakers are encouraged to apply to particular practical decisions. Although much of this literature examines the ethics of designing and developing AI and robotics, medical institutions typically must make purchase and deployment decisions about technologies that have already been designed and developed. The primary problem facing medical institutions is not one of ethical design but of ethical deployment. The purpose of this paper is to develop a practical model by which medical institutions may make ethical deployment decisions about ready-made advanced technologies. Our slogan is "more process, less principles." Ethically sound decisionmaking requires that the process by which medical institutions make such decisions include participatory, deliberative, and conservative elements. We argue that our model preserves the strengths of existing frameworks, avoids their shortcomings, and delivers its own moral, practical, and epistemic advantages. [ABSTRACT FROM AUTHOR]

The commercial determinants of health (CDoH) are attracting increased interest and are of great importance when discussing how trade affects health. Through a citation analysis of recent foundational CDoH documents (a Lancet paper series and an Oxford University textbook), we find that fully 71% of all citations reference the health sciences. The health sciences may be well suited to documenting the specific pathways of how commercial (by)products and practices harm human health. However, to operationalize upstream solutions for mitigating these harms, our citation analysis suggests that the field can engage political scientists, economists, sociologists, the trade law and business, as well as advocates in civil society and journalism, more so than it currently does. With CDoH explicitly referring to the interaction between commerce and health, CDoH researchers might be uniquely positioned to get health on the agenda of others, which requires that CDoH methods, datasets, evidence reviews, and proposed interventions are drawn from the widest possible range of sources. [ABSTRACT FROM AUTHOR]

In the health professions, altruism is a foundational value upon which professional privilege is built. This imperative towards self-sacrifice for the benefit of others is a key component of what it means to be professional. This paper explores how altruism operates as a coded mechanism of exclusion and oppression for disabled health professionals. Analysis is based on interviews with fifteen Canadian disabled healthcare professionals in medicine, nursing, occupational therapy, and social work about their experiences of inclusion and exclusion. Themes including the disproportionate sacrifice of time, resources, and income emerged, as did the need to manage political disclosure, often embodying the role of the 'super-crip' with patients/clients and colleagues so as to maintain others' faith in their professional competence and their professional privilege. Further discussion includes questions of how to 'crip' altruism as a professional value and the role of altruism as an ableist force within the health professions. Altruism, the idea of helping others even at cost to oneself, is an important value for health professionals. Disabled health professionals sacrifice more than non-disabled healthcare professionals to meet this obligation. Disabled healthcare professionals may work without accommodations, putting in extra time and effort to prove their altruism. Disabled healthcare professionals experience that disclosing disability may mean their colleagues will treat them as patients. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) has emerged as a transformative force in various sectors, including medicine and healthcare. Large language models like ChatGPT showcase AI's potential by generating human-like text through prompts. ChatGPT's adaptability holds promise for reshaping medical practices, improving patient care, and enhancing interactions among healthcare professionals, patients, and data. In pandemic management, ChatGPT rapidly disseminates vital information. It serves as a virtual assistant in surgical consultations, aids dental practices, simplifies medical education, and aids in disease diagnosis. A total of 82 papers were categorised into eight major areas, which are G1: treatment and medicine, G2: buildings and equipment, G3: parts of the human body and areas of the disease, G4: patients, G5: citizens, G6: cellular imaging, radiology, pulse and medical images, G7: doctors and nurses, and G8: tools, devices and administration. Balancing AI's role with human judgment remains a challenge. A systematic literature review using the PRISMA approach explored AI's transformative potential in healthcare, highlighting ChatGPT's versatile applications, limitations, motivation, and challenges. In conclusion, ChatGPT's diverse medical applications demonstrate its potential for innovation, serving as a valuable resource for students, academics, and researchers in healthcare. Additionally, this study serves as a guide, assisting students, academics, and researchers in the field of medicine and healthcare alike. [ABSTRACT FROM AUTHOR]

Background: Across the care economy there are major shortages in the health and care workforce, as well as high rates of attrition and ill-defined career pathways. The aim of this study was to evaluate current evidence regarding methods to improve care worker recruitment, retention, safety, and education, for the professional care workforce. Methods: A rapid review of comparative interventions designed to recruit, retain, educate and care for the professional workforce in the following sectors: disability, aged care, health, mental health, family and youth services, and early childhood education and care was conducted. Embase and MEDLINE databases were searched, and studies published between January 2015 and November 2022 were included. We used the Quality Assessment tool for Quantitative Studies and the PEDro tools to evaluate study quality. Results: 5594 articles were initially screened and after applying the inclusion and exclusion criteria, 30 studies were included in the rapid review. Studies most frequently reported on the professional nursing, medical and allied health workforces. Some studies focused on the single domain of care worker education (n = 11) while most focused on multiple domains that combined education with recruitment strategies, retention strategies or a focus on worker safety. Study quality was comparatively low with a median PEDro score of 5/10, and 77% received a weak rating on the Quality Assessment tool for Quantitative Studies. Four new workforce strategies emerged; early career rural recruitment supports rural retention; workload management is essential for workforce well-being; learning must be contextually relevant; and there is a need to differentiate recruitment, retention, and education strategies for different professional health and care workforce categories as needs vary. Conclusions: Given the critical importance of recruiting and retaining a strong health and care workforce, there is an immediate need to develop a cohesive strategy to address workforce shortfalls. This paper presents initial evidence on different interventions to address this need, and to inform care workforce recruitment and retention. Rapid Review registration PROSPERO 2022 CRD42022371721 Available from: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022371721 [ABSTRACT FROM AUTHOR]

The medical profession contains five "spheres of morality": clinical care, clinical research, scientific knowledge, population health, and the market. These distinct sets of normative commitments require physicians to act in different ways depending on the ends of the activity in question. For example, a physician-scientist emphasizes patients' well-being in clinic, prioritizes the scientific method in lab, and seeks to maximize shareholder returns as a board member of a pharmaceutical firm. Physicians increasingly occupy multiple roles in healthcare and move between them frequently, creating the possibility of conflict between the ethical obligations of their various roles. This paper examines the entire moral landscape of medicine through the lens of role morality. It develops a novel framework that helps physicians recognize how their moral commitments depend on the nature and context of the situation, clarifies ethical conflicts that physicians face, and concludes with ideas for resolving these conflicts. [ABSTRACT FROM AUTHOR]

The rapid rise of artificial intelligence (AI) in medicine in the last few years highlights the importance of developing bigger and better systems for data and model sharing. However, the presence of Protected Health Information (PHI) in medical data poses a challenge when it comes to sharing. One potential solution to mitigate the risk of PHI breaches is to exclusively share pre-trained models developed using private datasets. Despite the availability of these pre-trained networks, there remains a need for an adaptable environment to test and fine-tune specific models tailored for clinical tasks. This environment should be open for peer testing, feedback, and continuous model refinement, allowing dynamic model updates that are especially important in the medical field, where diseases and scanning techniques evolve rapidly. In this context, the Discovery Viewer (DV) platform was developed in-house at the Biomedical Engineering and Imaging Institute at Mount Sinai (BMEII) to facilitate the creation and distribution of cutting-edge medical AI models that remain accessible after their development. The all-in-one platform offers a unique environment for non-AI experts to learn, develop, and share their own deep learning (DL) concepts. This paper presents various use cases of the platform, with its primary goal being to demonstrate how DV holds the potential to empower individuals without expertise in AI to create high-performing DL models. We tasked three non-AI experts to develop different musculoskeletal AI projects that encompassed segmentation, regression, and classification tasks. In each project, 80% of the samples were provided with a subset of these samples annotated to aid the volunteers in understanding the expected annotation task. Subsequently, they were responsible for annotating the remaining samples and training their models through the platform's "Training Module". The resulting models were then tested on the separate 20% hold-off dataset to assess their performance. The classification model achieved an accuracy of 0.94, a sensitivity of 0.92, and a specificity of 1. The regression model yielded a mean absolute error of 14.27 pixels. And the segmentation model attained a Dice Score of 0.93, with a sensitivity of 0.9 and a specificity of 0.99. This initiative seeks to broaden the community of medical AI model developers and democratize the access of this technology to all stakeholders. The ultimate goal is to facilitate the transition of medical AI models from research to clinical settings. [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]

Purpose: The purpose of the paper "Bibliometric Analysis of ChatGPT's Applications in Medicine: A Comprehensive Assessment of its Impact and Potential" is to conduct a systematic evaluation of how ChatGPT, an AI language model, has been applied in the field of medicine. The study aims to assess the impact of ChatGPT's applications in medicine and explore its potential contributions to the healthcare domain. Materials and Methods: The Scopus database was selected and the search query (All (ChatGPT AND Medicine) was developed on 11, July 2023 to retrieve all the bibliographic records on the domine of interest. From each record, we retrieved data on the title, author, organizations, journals, publications type, source, country, collaboration, etc. They were exported to MS-Excel for bibliometric analysis and VOSviewer software was used for analyzing Co-Occurrence networks and the data and descriptive analysis were classified, collected one by one, and loaded into the Bibliometric R-package program to create science maps and statistical graphs. Results: ChatGPT - related Medicine papers in the Scopus database constitute 532 papers. these publications received 1046 citations, these authored by 1771 authors published 203 article type and etc. Average citations per document 1966 received and 111 (20.86%) received extremal funding support from 62+ research agencies supporting research in this area. selected 65 significant keywords appearing in ChatGPT and Medicine. USA and UK were contributed the highest papers. Medicine is the broad subject of the study were published highest number of papers (312). Conclusion: The findings from this study can help researchers, practitioners, and policymakers better understand the impact and potential of ChatGPT in advancing medical knowledge, patient care, and healthcare practices. Additionally, the paper may contribute to identifying knowledge gaps and guide further research in this rapidly evolving field at the intersection of AI and medicine. [ABSTRACT FROM AUTHOR]

Simple Summary: Neuroblastoma is a rare type of cancer that usually affects children. The high-risk patients' expected survival rate is less than 50%. One reason is the lack of precision in the standard treatment protocol: a one-size-fits-all multi-modal therapy. The study presented in this paper was designed to address this deficit by optimising the use of two chemotherapeutic agents—vincristine and cyclophosphamide—during induction chemotherapy—the part of the protocol that shrinks the primary tumour before surgical removal. We combined a mathematical model and an optimisation algorithm to identify the best chemotherapy schedules for a cohort of virtual patients with different initial tumour compositions. Our results reveal novel strategies to exploit a pair of drugs with different levels of efficacy, provide a platform on which to individualise induction chemotherapy, and lay the foundation for a personalised therapy that leverages targeted therapies, multi-region sequencing, liquid biopsies, and modern computational methods to improve today's multi-modal therapy. Neuroblastoma is the most common extra-cranial solid tumour in children. Despite multi-modal therapy, over half of the high-risk patients will succumb. One contributing factor is the one-size-fits-all nature of multi-modal therapy. For example, during the first step (induction chemotherapy), the standard regimen (rapid COJEC) administers fixed doses of chemotherapeutic agents in eight two-week cycles. Perhaps because of differences in resistance, this standard regimen results in highly heterogeneous outcomes in different tumours. In this study, we formulated a mathematical model comprising ordinary differential equations. The equations describe the clonal evolution within a neuroblastoma tumour being treated with vincristine and cyclophosphamide, which are used in the rapid COJEC regimen, including genetically conferred and phenotypic drug resistance. The equations also describe the agents' pharmacokinetics. We devised an optimisation algorithm to find the best chemotherapy schedules for tumours with different pre-treatment clonal compositions. The optimised chemotherapy schedules exploit the cytotoxic difference between the two drugs and intra-tumoural clonal competition to shrink the tumours as much as possible during induction chemotherapy and before surgical removal. They indicate that induction chemotherapy can be improved by finding and using personalised schedules. More broadly, we propose that the overall multi-modal therapy can be enhanced by employing targeted therapies against the mutations and oncogenic pathways enriched and activated by the chemotherapeutic agents. To translate the proposed personalised multi-modal therapy into clinical use, patient-specific model calibration and treatment optimisation are necessary. This entails a decision support system informed by emerging medical technologies such as multi-region sequencing and liquid biopsies. The results and tools presented in this paper could be the foundation of this decision support system. [ABSTRACT FROM AUTHOR]

Our intention is to contribute to the development of Canadian Nursing and Medical Education (NursMed) and efforts to redress deepening, intersecting health and social inequities. This paper addresses the following two research questions: (1) What are the ways in which Decolonial, Intersectional Pedagogies can inform Canadian NursMed Education with a focus on critically examining settler‐colonialism, health equity, and social justice? (2) What are the potential struggles and adaptations required to integrate Decolonial, Intersectional Pedagogies within Canadian NursMed Education in service of redressing intersecting health and social inequities? Briefly, Decolonial, Intersectional Pedagogies are philosophies of learning that encourage teachers and students to reflect on health through the lenses of settler‐colonialism, health equity, and social justice. Drawing on critical ethnographic research methods, we conducted in‐depth interviews with 25 faculty members and engaged in participant observation of classrooms in university‐based Canadian NursMed Education. The research findings are organized into three major themes, beginning with common institutional features influencing pedagogical approaches. The next set of findings addresses the complex strategies participants apply to integrate Decolonial, Intersectional Pedagogies. Lastly, the findings illustrate the emotional and spiritual toll some faculty members face when attempting to deliver Decolonial, Intersectional Pedagogies. We conclude that through the application of Decolonial, Intersectional Pedagogies teachers and students can support movements towards health equity, social justice, and unlearning/undoing settler‐colonialism. This study contributes new knowledge to stimulate dialog and action regarding the role of health professions education, specifically Nursing and Medicine as an upstream determinant of health in settler‐colonial nations such as Canada, United States, Australia, and New Zealand. [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: The integration of artificial intelligence (AI) into various fields has ushered in a new era of multidisciplinary progress. Defined as the ability of a system to interpret external data, learn from it, and adapt to specific tasks, AI is poised to revolutionize the world. In forensic medicine and pathology, algorithms play a crucial role in data analysis, pattern recognition, anomaly identification, and decision making. This review explores the diverse applications of AI in forensic medicine, encompassing fields such as forensic identification, ballistics, traumatic injuries, postmortem interval estimation, forensic toxicology, and more. Results: A thorough review of 113 articles revealed a subset of 32 papers directly relevant to the research, covering a wide range of applications. These included forensic identification, ballistics and additional factors of shooting, traumatic injuries, post-mortem interval estimation, forensic toxicology, sexual assaults/rape, crime scene reconstruction, virtual autopsy, and medical act quality evaluation. The studies demonstrated the feasibility and advantages of employing AI technology in various facets of forensic medicine and pathology. Conclusions: The integration of AI in forensic medicine and pathology offers promising prospects for improving accuracy and efficiency in medico-legal practices. From forensic identification to post-mortem interval estimation, AI algorithms have shown the potential to reduce human subjectivity, mitigate errors, and provide cost-effective solutions. While challenges surrounding ethical considerations, data security, and algorithmic correctness persist, continued research and technological advancements hold the key to realizing the full potential of AI in forensic applications. As the field of AI continues to evolve, it is poised to play an increasingly pivotal role in the future of forensic medicine and pathology. [ABSTRACT FROM AUTHOR]