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Though women increasingly make up the majority of medical-school and other science graduates, they remain a minority in academic biomedical settings, where they are less likely to hold leadership positions or be awarded research funding. A major factor is the career breaks that women disproportionately take to see to familial duties. They experience a related, but overlooked, hurdle upon their return: they are often too old to be eligible for 'early-career researcher' grants and 'career-development' awards, which are stepping stones to leadership positions in many institutions and which determine the demographics of their hierarchies for decades to come. Though age limits are imposed to protect young applicants from more experienced seniors, they have an unintended side effect of excluding returning workers, still disproportionately women, from the running. In this joint effort by the European Society of Clinical Microbiology and Infectious Diseases, the Federation of European Microbiological Societies, the Infectious Disease Society of America, the International Society for Infectious Diseases and the Swiss Society for Infectious Diseases, we invited all European Congress of Clinical Microbiology and Infectious Diseases-affiliated medical societies and funding bodies to participate in a survey on current 'early-career' application restrictions and measures taken to provide protections for career breaks. The following simple consensus recommendations are geared to funding bodies, academic societies and other organizations for the fair handling of eligibility for early-career awards: 1. Apply a professional, not physiological, age limit to applicants. 2. State clearly in the award announcement that career breaks will be factored into applicants' evaluations such that: • Time absent is time extended : for every full-time equivalent of career break taken, the same full-time equivalent will be extended to the professional age limit. • Opportunity costs will also be taken into account : people who take career breaks risk additional opportunity costs, with work that they did before the career break often being forgotten or poorly documented, particularly in bibliometric accounting. Although there is no standardized metric to measure additional opportunity costs, organizations should (a) keep in mind their existence when judging applicants' submissions, and (b) note clearly in the award announcement that opportunity costs of career breaks are also taken into account. 3. State clearly that further considerations can be undertaken, using more individualized criteria that are specific to the applicant population and the award in question. The working group welcomes feedback so that these recommendations can be improved and updated as needed. [ABSTRACT FROM AUTHOR]

One of the survivors in Spain of the free distribution press is the specialized publication Diario Médico, which has been disseminating health issues among professionals of the National Health System for 25 years. We did an exploratory-descriptive study about its origins and current situation, paying attention to its labour in paper, through the printed product, and in Red, through diariomedico.com. The techniques are the interview with its deputy director and the analysis of its products. The mixed format defines Diario Médico: it maintains its commitment to offer information on paper, despite having reduced the periodicity from daily to weekly; leads its paper readers to Orbyt, the digital press kiosk of the promoter group, Unidad Editorial, where it offers seven pages a day in pdf format with information for subscribers, and on the Web, with an edition that opens to the participation of the user. The informative tone of its contents and its usefulness for society, together with the growing interest of the non-specialized public in medicine and health, lead to Diario Médico, in our opinion, to have a double objective public: society in general and professionals of the System in particular. [ABSTRACT FROM AUTHOR]

Abstract Artificial intelligence (AI) is rapidly moving from an experimental phase to an implementation phase in many fields, including medicine. The combination of improved availability of large datasets, increasing computing power, and advances in learning algorithms has created major performance breakthroughs in the development of AI applications. In the last 5 years, AI techniques known as deep learning have delivered rapidly improving performance in image recognition, caption generation, and speech recognition. Radiology, in particular, is a prime candidate for early adoption of these techniques. It is anticipated that the implementation of AI in radiology over the next decade will significantly improve the quality, value, and depth of radiology's contribution to patient care and population health, and will revolutionize radiologists' workflows. The Canadian Association of Radiologists (CAR) is the national voice of radiology committed to promoting the highest standards in patient-centered imaging, lifelong learning, and research. The CAR has created an AI working group with the mandate to discuss and deliberate on practice, policy, and patient care issues related to the introduction and implementation of AI in imaging. This white paper provides recommendations for the CAR derived from deliberations between members of the AI working group. This white paper on AI in radiology will inform CAR members and policymakers on key terminology, educational needs of members, research and development, partnerships, potential clinical applications, implementation, structure and governance, role of radiologists, and potential impact of AI on radiology in Canada. [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]

Background: Adiponectin is an adipocyte-derived hormone that acts as a marker of insulin sensitivity. Bloodspot sampling by fingerstick onto filter paper may increase the feasibility of large-scale studies of the determinants of insulin sensitivity. We first describe the validation of an enzyme-linked immunoassay (ELISA) for quantifying adiponectin from dried blood spots and then demonstrate its application in a large trial (PROBIT). Methods: We quantified adiponectin from 3-mm diameter discs (≈3 µL of blood) punched from dried blood spots obtained from: i) whole blood standards (validation); and ii) PROBIT trial samples (application) in which paediatricians collected blood spots from 13,879 children aged 11.5 years from 31 sites across Belarus. We examined the distribution of bloodspot adiponectin by demographic and anthropometric factors, fasting insulin and glucose. Results: In the validation study, mean intra-assay coefficients of variation (n = 162) were 15%, 13% and 10% for ‘low’ (6.78 µg/ml), ‘medium’ (18.18 µg/ml) and 'high’ (33.13 µg/ml) internal quality control (IQC) samples, respectively; the respective inter-assay values (n = 40) were 23%, 21% and 14%. The correlation coefficient between 50 paired whole bloodspot versus plasma samples, collected simultaneously, was 0.87 (95% CI: 0.78 to 0.93). Recovery of known quantities of adiponectin (between 4.5 to 36 µg/ml) was 100.3–133%. Bloodspot adiponectin was stable for at least 30 months at −80°C. In PROBIT, we successfully quantified fasting adiponectin from dried blood spots in 13,329 of 13,879 (96%) children. Mean adiponectin (standard deviation) concentrations were 17.34 µg/ml (7.54) in boys and 18.41 µg/ml (7.92) in girls and were inversely associated with body mass index, fat mass, triceps and subscapular skin-fold thickness, waist circumference, height and fasting glucose. Conclusions: Bloodspot ELISA is suitable for measuring adiponectin in very small volumes of blood collected on filter paper and can be applied to large-scale studies. [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]

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]

Background: The psychometric properties of an online test are not necessarily identical to its paper and pencil original. The aim of this study is to test whether the factor structure of the Community Assessment of Psychic Experiences (CAPE) is measurement invariant with respect to online vs. paper and pencil assessment. Method: The factor structure of CAPE items assessed by paper and pencil (N = 796) was compared with the factor structure of CAPE items assessed by the Internet (N = 21,590) using formal tests for Measurement Invariance (MI). The effect size was calculated by estimating the Signed Item Difference in the Sample (SIDS) index and the Signed Test Difference in the Sample (STDS) for a hypothetical subject who scores 2 standard deviations above average on the latent dimensions. Results: The more restricted Metric Invariance model showed a significantly worse fit compared to the less restricted Configural Invariance model (χ2(23) = 152.75, p<0.001). However, the SIDS indices appear to be small, with an average of −0.11. A STDS of −4.80 indicates that Internet sample members who score 2 standard deviations above average would be expected to score 4.80 points lower on the CAPE total scale (ranging from 42 to 114 points) than would members of the Paper sample with the same latent trait score. Conclusions: Our findings did not support measurement invariance with respect to assessment method. Because of the small effect sizes, the measurement differences between the online assessed CAPE and its paper and pencil original can be neglected without major consequences for research purposes. However, a person with a high vulnerability for psychotic symptoms would score 4.80 points lower on the total scale if the CAPE is assessed online compared to paper and pencil assessment. Therefore, for clinical purposes, one should be cautious with online assessment of the CAPE. [ABSTRACT FROM AUTHOR]

Recently, there has been a growing emphasis on basic number processing competencies (such as the ability to judge which of two numbers is larger) and their role in predicting individual differences in school-relevant math achievement. Children’s ability to compare both symbolic (e.g. Arabic numerals) and nonsymbolic (e.g. dot arrays) magnitudes has been found to correlate with their math achievement. The available evidence, however, has focused on computerized paradigms, which may not always be suitable for universal, quick application in the classroom. Furthermore, it is currently unclear whether both symbolic and nonsymbolic magnitude comparison are related to children’s performance on tests of arithmetic competence and whether either of these factors relate to arithmetic achievement over and above other factors such as working memory and reading ability. In order to address these outstanding issues, we designed a quick (2 minute) paper-and-pencil tool to assess children’s ability to compare symbolic and nonsymbolic numerical magnitudes and assessed the degree to which performance on this measure explains individual differences in achievement. Children were required to cross out the larger of two, single-digit numerical magnitudes under time constraints. Results from a group of 160 children from grades 1–3 revealed that both symbolic and nonsymbolic number comparison accuracy were related to individual differences in arithmetic achievement. However, only symbolic number comparison performance accounted for unique variance in arithmetic achievement. The theoretical and practical implications of these findings are discussed which include the use of this measure as a possible tool for identifying students at risk for future difficulties in mathematics. [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]

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]

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]

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]

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]

Informed consent is the cornerstone of human research subject protection. Many subjects sign consent documents without understanding the study purpose, procedures, risks, benefits, and their rights. Proof of comprehension is not required and rarely obtained. Understanding might improve by using an interactive system with multiple options for hearing, viewing and reading about the study and the consent form at the subject’s own pace with testing and immediate feedback. This prospective randomized study compared the IRB-approved paper ICF for an actual clinical research study with an interactive presentation of the same study and its associated consent form using an iPad device in two populations: clinical research professionals, and patients drawn from a variety of outpatient practice settings. Of the 90 participants, 69 completed the online test and survey questions the day after the session (maximum 36 hours post-session). Among research professionals (n = 14), there was a trend (p  = .07) in the direction of iPad subjects testing better on the online test (mean correct  =  77%) compared with paper subjects (mean correct  =  57%). Among patients (n = 55), iPad subjects had significantly higher test scores than standard paper consent subjects (mean correct  =  75% vs 58%, p < .001). For all subjects, the total time spent reviewing the paper consent was 13.2 minutes, significantly less than the average of 22.7 minutes total on the three components to be reviewed using the iPad (introductory video, consent form, interactive quiz). Overall satisfaction and overall enjoyment slightly favored the interactive iPad presentation. This study demonstrates that combining an introductory video, standard consent language, and an interactive quiz on a tablet-based system improves comprehension of research study procedures and risks. [ABSTRACT FROM AUTHOR]

Over the years, the Bio-Ontologies SIG at ISMB has provided a forum for discussion of the latest and most innovative research in the application of ontologies and more generally the organisation, presentation and dissemination of knowledge in biomedicine and the life sciences. The ten papers selected for this supplement are extended versions of the original papers presented at the 2010 SIG. The papers span a wide range of topics including practical solutions for data and knowledge integration for translational medicine, hypothesis based querying , understanding kidney and urinary pathways, mining the pharmacogenomics literature; theoretical research into the orthogonality of biomedical ontologies, the representation of diseases, the representation of research hypotheses, the combination of ontologies and natural language processing for an annotation framework, the generation of textual definitions, and the discovery of gene interaction networks. [ABSTRACT FROM AUTHOR]

The article offers information on the updated position paper on the policies relating to HIV infection in the U.S. The position paper on HIV policy has been established in collaboration with the HIV Medicine Association of the Infectious Diseases Society of America and the American College of Physicians. The updated HIV policy highlights major advances on the treatment of HIV infection, the expansion of HIV as a pandemic and the prevalence of HIV transmission in health care settings. Details on these updates emphasizing public health and clinical imperatives in identifying HIV infection are discussed.

Over the 15 years, the Bio-Ontologies SIG at ISMB has provided a forum for discussion of the latest and most innovative research in the bio-ontologies development, its applications to biomedicine and more generally the organisation, presentation and dissemination of knowledge in biomedicine and the life sciences. The seven papers and the commentary selected for this supplement span a wide range of topics including: web-based querying over multiple ontologies, integration of data, annotating patent records, NCBO Web services, ontology developments for probabilistic reasoning and for physiological processes, and analysis of the progress of annotation and structural GO changes. [ABSTRACT FROM AUTHOR]

We describe a method that uses crowdsourced postcode coordinates and Google maps to estimate average distance and travel time for inhabitants of a municipality to a casualty clinic in Norway. The new method was compared with methods based on population centroids, median distance and town hall location, and we used it to examine how distance affects the utilisation of out-of-hours primary care services. At short distances our method showed good correlation with mean travel time and distance. The utilisation of out-of-hours services correlated with postcode based distances similar to previous research. The results show that our method is a reliable and useful tool for estimating average travel distances and travel times. [ABSTRACT FROM AUTHOR]

Over the 14 years, the Bio-Ontologies SIG at ISMB has provided a forum for discussion of the latest and most innovative research in the bio-ontologies development, its applications to biomedicine and more generally the organisation, presentation and dissemination of knowledge in biomedicine and the life sciences. The seven papers selected for this supplement span a wide range of topics including: web-based querying over multiple ontologies, integration of data from wikis, innovative methods of annotating and mining electronic health records, advances in annotating web documents and biomedical literature, quality control of ontology alignments, and the ontology support for predictive models about toxicity and open access to the toxicity data. [ABSTRACT FROM AUTHOR]

The article presents a study on the efficiency of handheld computers in storing data on medicine. This study compared the completeness of data collection using paper forms and electronic forms loaded on handheld computers in an office-based patient interview survey which was held within the American Academy of Family Physicians National Research Network. It was established that these computers were not superior in storing information because of the presence of technical difficulties.

This paper has been substantially revised by the Canadian Psychiatric Association's Research Committee and approved for republication by the CPA's Board of Directors on May 3, 2017. The original policy paper1 was developed by the Scientific and Research Affairs Standing Committee and approved by the Board of Directors on November 10, 2008. [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]

Howey and O'Shea (2006) believe they have demonstrated the prehistoric manifestation of a particular Ojibwa Midewiwin origin story in the arrangement of features at an archaeological site in Michigan, thereby negating ethnohistorical arguments that the Midewiwin was of post-European-contact origin. The authors also believe they have shown that explaining past ritual behavior "can be derived from archaeological data alone." There is ample information in their own argument to disallow such claims. [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 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]

Reports the effectiveness of the statistical assessment scheme for papers submitted to the 'British Medical Journal,'. Statistical criticism of the content; Comparison of reports on published and unpublished papers; Acceptability of assessed papers.

This paper discusses the state of advancement in the development of spectroscopic methods based on the use of mid (proper) infrared radiation in the context of applications in various fields of science and technology. The authors drew attention to the most important solutions specific to both spectroscopy itself (ATR technique) and chemometric data processing tools (PCA and PLS models). The objective of the current paper is to collect and consistently present information on various aspects of FT-IR spectroscopy, which is not only a well-known and well-established method but is also continuously developing. The innovative aspect of the current review is to show FT-IR's great versatility that allows its applications to solve and explain issues from both the scientific domain (e.g., hydrogen bonds) and practical ones (e.g., technological processes, medicine, environmental protection, and food analysis). Particular attention was paid to the issue of hydrogen bonds as key non-covalent interactions, conditioning the existence of living matter and determining the number of physicochemical properties of various materials. Since the role of FT-IR spectroscopy in the field of hydrogen bond research has great significance, a historical outline of the most important qualitative and quantitative hydrogen bond theories is provided. In addition, research on selected unconventional spectral effects resulting from the substitution of protons with deuterons in hydrogen bridges is presented. The state-of-the-art and originality of the current review are that it presents a combination of uses of FT-IR spectroscopy to explain the way molecules vibrate and the effects of those vibrations on macroscopic properties, hence practical applications of given substances. [ABSTRACT FROM AUTHOR]

The paper examines the concept of Tamil siddha literature as an integrating force for the local cultural ecosystem. The research is based on texts ascribed to two prominent authors of Tamil siddha tradition, namely Siddhar Yākōpu and Siddhar Pōkar (ca. 17th cent.). The first part of the paper looks at representations of nature in the Siddhars' texts, and demonstrates that the authors attribute certain extraordinary powers and divinity to nature. This further suggests that such views on nature allow the Siddhars to interconnect different realms typically viewed as separate in the contemporary secular perspective where liberatory practices are positioned apart from domains like nature and medicine. Attempts to integrate various fields of siddha lore are evident in the Siddhars' texts, for instance, in Vaittiya Kallāṭam, which is analyzed in the second section of the paper. To this end, among others, the perspective of material ecocriticism is applied to examine the images of natural material substances in Tamil siddha texts. [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]

Machine learning (ML), artificial neural networks (ANNs), and deep learning (DL) are all topics that fall under the heading of artificial intelligence (AI) and have gained popularity in recent years. ML involves the application of algorithms to automate decision-making processes using models that have not been manually programmed but have been trained on data. ANNs that are a part of ML aim to simulate the structure and function of the human brain. DL, on the other hand, uses multiple layers of interconnected neurons. This enables the processing and analysis of large and complex databases. In medicine, these techniques are being introduced to improve the speed and efficiency of disease diagnosis and treatment. Each of the AI techniques presented in the paper is supported with an example of a possible medical application. Given the rapid development of technology, the use of AI in medicine shows promising results in the context of patient care. It is particularly important to keep a close eye on this issue and conduct further research in order to fully explore the potential of ML, ANNs, and DL, and bring further applications into clinical use in the future. [ABSTRACT FROM AUTHOR]

Augmented reality (AR) is one of the latest innovations taking route into various markets which include gaming, medicine, automotive, retail amongst others. AR technology has been in development since the 1960's. AR technology lets users see the real world and projects digital information onto the existing environment. In many ways, AR is a mixture of Virtual reality, imposed into real life. These virtual contents are typically in the form of digital imagery or sound, usually applied in 3D models or videos. AR works via the use of a range of sensors such as a camera, computer components or a display device. Particularly, augmented reality can be a more promising technique of a surgery which requires great precision. This paper introduces an overview of augmented reality and reviews the recent applications in medicine. [ABSTRACT FROM AUTHOR]

Objective: In 2002, the National Library of Medicine (NLM) introduced semi-automated indexing of Medline using the Medical Text Indexer (MTI). In 2021, NLM announced that it would fully automate its indexing in Medline with an improved MTI by mid-2022. This pilot study examines indexing using a sample of records in Medline from 2000, and how an early, public version of MTI's outputs compares to records created by human indexers. Methods: This pilot study examines twenty Medline records from 2000, a year before the MTI was introduced as a MeSH term recommender. We identified twenty higher- and lower-impact biomedical journals based on Journal Impact Factor (JIF) and examined the indexing of papers by feeding their PubMed records into the Interactive MTI tool. Results: In the sample, we found key differences between automated and human-indexed Medline records: MTI assigned more terms and used them more accurately for citations in the higher JIF group, and MTI tended to rank the Male check tag more highly than the Female check tag and to omit Aged check tags. Sometimes MTI chose more specific terms than human indexers but was inconsistent in applying specificity principles. Conclusion: NLM's transition to fully automated indexing of the biomedical literature could introduce or perpetuate inconsistencies and biases in Medline. Librarians and searchers should assess changes to index terms, and their impact on PubMed's mapping features for a range of topics. Future research should evaluate automated indexing as it pertains to finding clinical information effectively, and in performing systematic searches. [ABSTRACT FROM AUTHOR]

Background: The last few decades have witnessed increased entry of women in the medical workforce both in High and Low income countries. This increased female participation in medicine is often called as 'feminisation of medicine'. There is not much research available on medical workforce feminisation and its potential consequences in resource constrained countries. This paper analyses Pakistani physicians' perceptions regarding feminisation of medical workforce and its implications for human resources for health policies and practice in Pakistan. Materials & Methods: A phenomenological research design was used to conduct thirteen semi-structured telephone interviews with Pakistani physicians to explore their perceptions regarding feminisation of medical workforce and its implications. Both purposive and snow-ball sampling techniques was used. Data analysis was done by using thematic analysis technique. Results: The main reasons for feminisation are open-merit policy for admission in medical schools, to get good matches and medicine as an acceptable profession for females. There was a difference of perceptions about medical workforce feminisation on the accessibility of medical services in Pakistan. Majority did not agree that more female doctors will increase Pakistani women's accessibility to doctors, especially in rural areas. This may not happen unless the feminised medical workforce is properly managed and incentivised. Conclusion: The volume of female doctors in Pakistan is gradually increasing which have important implications for policy and practice of medicine. Research is needed to understand these reasons and to know Pakistan health system's ability to meet the needs and requirements of females as the main healthcare providers. [ABSTRACT FROM AUTHOR]

Presents tips of writing a medical paper in Great Britain. Identification of writing the concluding part as a helpful step for an easy paper formulation; Disadvantages of concentrating on the introductory part of the paper; Significance of formulating an interesting title.

Introduction: the formation of the medical professional identity is achieved in stages during which the characteristics, values and norms of the medical profession are internalized, which results in the individual thinking, acting and feeling like a doctor. Tutors in medicine should clarify and encourage the principles within study programs and learning environments in order to support the formation of the professional identity of their students. Objective: the purpose of this paper is to reveal the participation of medical tutoring as one of the most influential factors that contribute to the development of the professional identity of medical students, as well as to give some guidelines so that the training of tutors. It contemplates tools that allow them to contribute to the positive and valued construction of the professional identity of the students. [ABSTRACT FROM AUTHOR]

One problem in the quantitative assessment of biomechanical impairments in Parkinson's disease patients is the need for scalable and adaptable computing systems. This work presents a computational method that can be used for motor evaluations of pronation-supination hand movements, as described in item 3.6 of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS). The presented method can quickly adapt to new expert knowledge and includes new features that use a self-supervised training approach. The work uses wearable sensors for biomechanical measurements. We tested a machine-learning model on a dataset of 228 records with 20 indicators from 57 PD patients and eight healthy control subjects. The test dataset's experimental results show that the method's precision rates for the pronation and supination classification task achieved up to 89% accuracy, and the F1-scores were higher than 88% in most categories. The scores present a root mean squared error of 0.28 when compared to expert clinician scores. The paper provides detailed results for pronation-supination hand movement evaluations using a new analysis method when compared to the other methods mentioned in the literature. Furthermore, the proposal consists of a scalable and adaptable model that includes expert knowledge and affectations not covered in the MDS-UPDRS for a more in-depth evaluation. [ABSTRACT FROM AUTHOR]

Chitosan derived from chitin gas gathered much interest as a biopolymer due to its known and possible broad applications. Chitin is a nitrogen-enriched polymer abundantly present in the exoskeletons of arthropods, cell walls of fungi, green algae, and microorganisms, radulae and beaks of molluscs and cephalopods, etc. Chitosan is a promising candidate for a wide variety of applications due to its macromolecular structure and its unique biological and physiological properties, including solubility, biocompatibility, biodegradability, and reactivity. Chitosan and its derivatives have been known to be applicable in medicine, pharmaceuticals, food, cosmetics, agriculture, the textile and paper industries, the energy industry, and industrial sustainability. More specifically, their use in drug delivery, dentistry, ophthalmology, wound dressing, cell encapsulation, bioimaging, tissue engineering, food packaging, gelling and coating, food additives and preservatives, active biopolymeric nanofilms, nutraceuticals, skin and hair care, preventing abiotic stress in flora, increasing water availability in plants, controlled release fertilizers, dye-sensitised solar cells, wastewater and sludge treatment, and metal extraction. The merits and demerits associated with the use of chitosan derivatives in the above applications are elucidated, and finally, the key challenges and future perspectives are discussed in detail. [ABSTRACT FROM AUTHOR]

The methods of additive manufacturing of anatomical models are widely used in medical practice, including physician support, education and planning of treatment procedures. The aim of the review was to identify the area of additive manufacturing and the application of anatomical models, imitating both soft and hard tissue. The paper outlines the most commonly used methodologies, from medical imaging to obtaining a functional physical model. The materials used to imitate specific organs and tissues, and the related technologies used to produce, them are included. The study covers publications in English, published by the end of 2022 and included in the Scopus. The obtained results emphasise the growing popularity of the issue, especially in the areas related to the attempt to imitate soft tissues with the use of low-cost 3D printing and plastic casting techniques. [ABSTRACT FROM AUTHOR]

Nanotechnology, contrary to its name, has massively revolutionized industries around the world. This paper predominantly deals with data regarding the applications of nanotechnology in the modernization of several industries. A comprehensive research strategy is adopted to incorporate the latest data driven from major science platforms. Resultantly, a broad-spectrum overview is presented which comprises the diverse applications of nanotechnology in modern industries. This study reveals that nanotechnology is not limited to research labs or small-scale manufacturing units of nanomedicine, but instead has taken a major share in different industries. Companies around the world are now trying to make their innovations more efficient in terms of structuring, working, and designing outlook and productivity by taking advantage of nanotechnology. From small-scale manufacturing and processing units such as those in agriculture, food, and medicine industries to larger-scale production units such as those operating in industries of automobiles, civil engineering, and environmental management, nanotechnology has manifested the modernization of almost every industrial domain on a global scale. With pronounced cooperation among researchers, industrialists, scientists, technologists, environmentalists, and educationists, the more sustainable development of nano-based industries can be predicted in the future. [ABSTRACT FROM AUTHOR]

The aim of this paper is to present an analysis of the academic leagues in health and spirituality, a space that predominates in training on the subject in Brazil. It seeks to analyze how the training provided by these organizations in spirituality is secular, not only due to the way spirituality is mobilized but also because of the specific characteristics of the health configuration. On one hand, since the emergence of medical leagues, there have been observable connections with religion, even though they were initially inspired by science in the early 20th century. On the other hand, various religious connections can be recognized, whether in people's life trajectories or in the formation of health and spirituality leagues. In this manner, we comprehend the emergence of leagues affiliated with the Academic Association of Leagues and Study Groups in Spirituality and Health (AALEGREES), with a particular focus on their secular configurations. [ABSTRACT FROM AUTHOR]

When the COVID-19 pandemic struck and China reported the first case to the World Health Organization in December 2019, there was no evidence-based treatment to combat it. With the catastrophic situation that followed, materialised by a considerable number of deaths, researchers, doctors, traditional healers, and governments of all nations committed themselves to find therapeutic solutions, including preventive and curative. There are effective treatments offered both by modern medicine and traditional medicine for COVID-19 today. However, other therapeutic proposals have not been approved due to the lack of effectiveness and scientific rigour during their development process. Proponents of modern medicine prefer biomedical therapies while in some countries, traditional treatments are used regularly because of their availability, affordability and satisfaction they bring to the population. In this paper, we propose a transactional medicine approach where the interaction between traditional and modern medicine produces a change. With this approach, the promoters of traditional medicine and those of modern medicine will be able to acquire knowledge through the experience produced by their encounters. Transactional medicine aims to be a model for decolonising medicine and recognising the value of both traditional and modern medicine in the fight against COVID-19 and other global emerging pathogens. [ABSTRACT FROM AUTHOR]

Spices have been an integral part of the trade of medieval Kerala since the ancient times. Greeks, Romans, Chinese, Jews, Arabs and Europeans were part of the spice trade in the region. Having been recognised for their healing properties, spices have been used widely as medicines in the regions that they were traded in. This paper is an attempt at understanding the circulation and incorporation of indigenous knowledge regarding spices as medicine and its subsequent usage in the medical realm of western pharmacopoeia. Medieval Kerala has had an active tradition of plant-based medicine with the focus mainly on spices. The works of van Rheede and de Orta attest to the local knowledge on botany and its application in medicine. The article focuses on bringing out the influence that the local medical traditions and knowledge have had on western medical corpus and to understand the acceptance and acknowledgement they received for the same. [ABSTRACT FROM AUTHOR]

Health literacy has pushed the frontiers of self-care in recent decades, particularly among older adults. However, not much is known about self-medication for minor ailments and chronic conditions among older adults in developing countries. This paper addresses this knowledge gap by examining the prevalence, patterns, and associated factors of self-medication among older adults (aged 50 years and more) in Ghana. The study employed a cross-sectional survey within four communities in the Bosomtwe District, Ghana. Using the purposive, snowballing, and convenient techniques, 384 older adults were involved in the study. Multivariate logistic regressions were used to estimate the factors associated with self-medication. Up to 54.4% of the respondents had self-medicated at least 3 months before the survey, while 60.2% self-medicated at least once every month. Open markets (43%) were the dominant drug sources, while quick relief (26.6%) and cheap cost (22.7%) were the reasons for self-medication. Females (AOR: 2.626, CI: 0.015-0.030, p = 0.022), tertiary graduates (AOR: 1.825, CI: 0.007-0.045, p = 0.045) and uninsured older adults (AOR: 3.293, CI: 0.015-0.026, p = 0.007) were more likely to self-medicate. Furthermore, those with no past illness (AOR: 0.036, CI: 0.007-0.033, p = 0.013) and without non-communicable disease (AOR: 0.008, CI: 0.001-0.012, p = 0.020) were less likely to self-medicate. Policy recommendations targeting the educated, uninsured, female older adults as well as stiffening the sale of medicines without prescription will be necessary for reducing the prevalence of self-medication among older adults. Subjects: Health & Development; Aging; Aging and Health; Health Education and Promotion [ABSTRACT FROM AUTHOR]

• medBERT.de : German BERT model tailored for medical domain expertise. • Trained using 4.7 million diverse medical documents for optimal results. • Achieved new state-of-the-art on eight medical NLP benchmarks. • Efficient tokenization has minor role, focus on domain-specific training. • Public release of pre-trained model weights and new benchmarks for research. This paper presents medBERT.de , a pre-trained German BERT model specifically designed for the German medical domain. The model has been trained on a large corpus of 4.7 Million German medical documents and has been shown to achieve new state-of-the-art performance on eight different medical benchmarks covering a wide range of disciplines and medical document types. In addition to evaluating the overall performance of the model, this paper also conducts a more in-depth analysis of its capabilities. We investigate the impact of data deduplication on the model's performance, as well as the potential benefits of using more efficient tokenization methods. Our results indicate that domain-specific models such as medBERT.de are particularly useful for longer texts, and that deduplication of training data does not necessarily lead to improved performance. Furthermore, we found that efficient tokenization plays only a minor role in improving model performance, and attribute most of the improved performance to the large amount of training data. To encourage further research, the pre-trained model weights and new benchmarks based on radiological data are made publicly available for use by the scientific community. [ABSTRACT FROM AUTHOR]

Nowadays in our society modern science uses a wide range of materials to perform multiple functions. One of the fields in which biological, synthetic and hybrid materials have found various applications is related to the medical one. The variety of materials used in medicine adapts to specific requirements and applications, due to the wide range of physical, chemical and biological properties that these materials can guarantee. The present review paper offers a short review, based on the data available in the scientific literature, on the possibility of using materials for dental application. [ABSTRACT FROM AUTHOR]

Background: Maintaining a health professional workforce in rural and remote areas poses a significant challenge internationally. A range of recruitment and retention strategies have had varying success and these are  generally developed from the collective experience of all health professions, rather than targeted to professional groups with differing educational and support contexts. This review explores, compares and synthesises the evidence examining the experience of early career rural and remote allied health professionals and doctors to better understand both the profession specific, and common factors that influence their experience.Methods: Qualitative studies that include early career allied health professionals' or doctors' experiences of working in rural or remote areas and the personal and professional factors that impact on this experience were considered. A systematic search was completed across five databases and three grey literature repositories to identify published and unpublished studies. Studies published since 2000 in English were considered. Studies were screened for inclusion and critically appraised by two independent reviewers. Data was extracted and assigned a level of credibility. Data synthesis adhered to the JBI meta-aggregative approach.Results: Of the 1408 identified articles, 30 papers were eligible for inclusion, with one rated as low in quality and all others moderate or high quality. A total of 23 categories, 334 findings and illustrations were aggregated into three synthesised findings for both professional groups including: making a difference through professional and organisational factors, working in rural areas can offer unique and rewarding opportunities for early career allied health professionals and doctors, and personal and community influences make a difference. A rich dataset was obtained and findings illustrate similarities including the need to consider personal factors, and differences, including discipline specific supervision for allied health professionals and local supervision for doctors.Conclusions: Strategies to enhance the experience of both allied health professionals and doctors in rural and remote areas include enabling career paths through structured training programs, hands on learning opportunities, quality supervision and community immersion.Systematic Review Registration Number: PROSPERO CRD42021223187. [ABSTRACT FROM AUTHOR]