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Copyright of Journal of College of Sharia & Islamic Studies is the property of Qatar University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purpose: Nowadays, many studies discuss scholarly publishing and associated challenges, but the problem of hijacked journals has been neglected. Hijacked journals are cloned websites that mimic original journals but are managed by cybercriminals. The present study uses a topic modeling approach to analyze published papers in hijacked versions of medical journals. Methods: A total of 3384 papers were downloaded from 21 hijacked journals in the medical domain and analyzed by topic modeling algorithm. Results: Results indicate that hijacked versions of medical journals are published in most fields of the medical domain and typically respect the primary domain of the original journal. Conclusion: The academic world is faced with the third-generation of hijacked journals, and their detection may be more complex than common ones. The usage of artificial intelligence (AI) can be a powerful tool to deal with the phenomenon. [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]

Diversity, flexibility, easy accessibility, broad continuing acceptance in developing countries and increasing popularity in developed countries, relative low cost, low levels of technological input, relative low side effects, and growing economic importance are some of the positive features of traditional medicine. In rural India, traditional medicine continues to be the only available form of care. Many communities continue to treat patients using their old methods, unaffected by contemporary medical advancements. Due to their accessibility, affordability, and ease of use, tribal tribes prefer to utilize and consult their own traditional healers. These are likewise thought to be highly effective and without any adverse effects. This paper aims to identify various traditional medicines used for treating illness and infirmities, by taking accounts from the residents of Chungtlang village, Mamit District, Mizoram. The objective here lies in discovering traditional knowledge of medicinal plants and their uses for various infirmities. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Prevention & Treatment For Stomatological Diseases is the property of Journal of Prevention & Treatment For Stomatological Diseases Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

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]

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]

Copyright of Tiempos Modernos is the property of Tiempos Modernos and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

Background: Anticoagulation therapy plays a crucial role in the management of atrial fibrillation (AF) by significantly reducing the risk of stroke. Direct oral anticoagulants (DOAC) became preferred over warfarin due to their superior safety and efficacy profile. Assessing adherence to anticoagulation therapy is necessary in clinical practice for optimising patient outcomes and treatment efficacy, thus emphasising its significance. Methods: A retrospective study utilised the Latvian National Health Service reimbursement prescriptions database, covering prescriptions for AF and flutter from January 2012 to December 2022. The proportion of days covered method was selected for adherence assessment, categorising it into three groups: (1) below 80%, (2) between 80% and 90%, and (3) above 90%. Results: A total of 1,646,648 prescriptions were analysed. Dabigatran prescriptions started declining after 2020, coinciding with a decrease in warfarin prescriptions since 2018. The total adherence levels to DOAC therapy were 69.4%. Only 44.2% of users achieved an adherence level exceeding 80%. The rate of paper prescriptions decreased from 98.5% in 2017 to 1.3% in 2022. Additionally, the utilisation of international non-proprietary names reached 79.7% in 2022. Specifically, 16.7% of patients selected a single pharmacy, whereas 27.7% visited one or two pharmacies. Meanwhile, other patients obtained medicines from multiple pharmacies. Conclusions: The total adherence level to DOAC therapy is evaluated as low and there was no significant difference in age, gender, or "switcher" status among adherence groups. Physicians' prescribing habits have changed over a decade. [ABSTRACT FROM AUTHOR]

Breast cancer is an illness that affects many women and can cause even death; this is a case of not being detected on time, which could be due to a human error during the analysis of radiographic images or not going on time in a health center. For this, using machine learning (ML) to analyze radiographic images is proposed as a support tool for radiologists aiming to reduce false diagnostic rates. While researching information, it was detected that this technology has many benefits in the health area; however, it also has limitations or disadvantages. The importance of this paper is to demonstrate that there are not enough clinical tests nor details about the methodologies that were used; there should be more to assert that ML is defined at the moment of making a diagnosis, which generates no conclusive results regarding effectiveness and therefore creates mistrust in doctors, and some people might rather use deep learning (DL) for its application in the detection of breast cancer because DL has more practical tests and fewer limitations than machine learning. [ABSTRACT FROM AUTHOR]

Biomedicine is constantly evolving to ensure a significant and positive impact on healthcare, which has resulted in innovative and distinct requisites such as hydrogels. Chitosan-based formulations stand out for their versatile utilization in drug encapsulation, transport, and controlled release, which is complemented by their biocompatibility, biodegradability, and non-immunogenic nature. Stimuli-responsive hydrogels, also known as smart hydrogels, have strictly regulated release patterns since they respond and adapt based on various external stimuli. Moreover, they can imitate the intrinsic tissues' mechanical, biological, and physicochemical properties. These characteristics allow stimuli-responsive hydrogels to provide cutting-edge, effective, and safe treatment. Constant progress in the field necessitates an up-to-date summary of current trends and breakthroughs in the biomedical application of stimuli-responsive chitosan-based hydrogels, which was the aim of this review. General data about hydrogels sensitive to ions, pH, redox potential, light, electric field, temperature, and magnetic field are recapitulated. Additionally, formulations responsive to multiple stimuli are mentioned. Focusing on chitosan-based smart hydrogels, their multifaceted utilization was thoroughly described. The vast application spectrum encompasses neurological disorders, tumors, wound healing, and dermal infections. Available data on smart chitosan hydrogels strongly support the idea that current approaches and developing novel solutions are worth improving. The present paper constitutes a valuable resource for researchers and practitioners in the currently evolving field. [ABSTRACT FROM AUTHOR]

This scientific paper aims to identify the links between the use of social networking sites and the professional performance of employees in the medical field, as well as the negative side effects arising from the use of social networks, including the emergence of social network addiction and anxiety disorders or personality, especially in the post-pandemic period of COVID-19. The research indicated a significant relationship, i.e., a weak positive correlation between the use of social networks, and Internet and social network addiction. Correlations were found between the mediators belonging to the secondary effects of social media use and employee performance. According to the model developed by the author, participants who reported higher levels of anxiety disorders or internet addictions reported lower levels of performance. Those addictions are significantly related to both social media use and individual performance, and thus meets at least some of the criteria for being a mediator. [ABSTRACT FROM AUTHOR]

Copyright of GMS Journal for Medical Education is the property of German Medical Science Publishing House gGmbH and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The medical metaverse and digital twin are set to revolutionise healthcare. Like all emerging technologies their benefits must be weighed against their ethical and social, impacts. If we consider the advances of medical technology as an expression of our values, such as the pursuit of knowledge, cures and healing, an ethical study allows us to align our values and steer the technology towards an agreed goal. However, to appreciate the long-term consequents of a technology, those consequences must be considered in the context of a society already shaped by that technology. This paper identifies the technologies currently shaping society and considers the ethical, and social consequences of the medical metaverse and digital twin in that future society. [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]

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]

Background: Lifestyle has become a major and well‐recognized aspect of modern healthcare, but there is little awareness of the origins of lifestyle medicine. Results: This paper shows that a major contribution to lifestyle medicine was made by Greco‐Roman physicians. Ancient Greek and Roman doctors placed considerable emphasis on the role lifestyle played in determining the state of their patients' health. [ABSTRACT FROM AUTHOR]

In Antarctica, it is extremely difficult to organise medical evacuations in winter. Antarctic physicians are often alone and must be prepared to perform surgery and dentistry, even if they are not specialists. This scoping review summarises epidemiological data on the types of surgical procedures performed in Antarctica and identifies gaps in the literature in this area. We searched PubMed and Google Scholar, without language restriction, for papers published between 1 January 1904, and 1 February 2022. Of the 35 papers on 12 Antarctic programs, very few were retrospective observational epidemiological studies; the majority were medical reports. The search identified 41 surgical procedures or reasons for surgical consultation, 19 different reasons for medical evacuations, and 12 causes of death that may have required surgical management. The diagnostic classifications used and the prevalence of each reported surgical speciality were heterogeneous. The most cited specialities were orthopaedics, dentistry, and digestive surgery. Telemedicine was integrated into on-site care or medical evacuation decisions. The current literature is poor, and most studies do not apply to surgical issues. The heterogeneous data collection methodologies limit their interpretation. A standardised diagnostic classification and detailed and systematic epidemiological registers will help define the contours of surgical management in Antarctica. [ABSTRACT FROM AUTHOR]

Extracellular vesicles in wound healing have become an active research field with substantial value and potential. Nevertheless, there are few bibliometric studies in this field. We aimed to visualise the research hot spots and trends of extracellular vesicles in wound healing using a bibliometric analysis to help understand the future development of basic and clinical research. The articles and reviews regarding extracellular vesicles in the wound healing were selected from the Web of Science Core Collection. VOSviewers, CiteSpace and R package "bibliometric" were used to conduct this bibliometric analysis. A total of 1225 articles from 56 countries led by China and the United States were included. The number of publications related to extracellular vesicles increased year by year. Shanghai Jiaotong University, Huazhong University of Science and Technology, Sun Yat‐sen University and Central South University are the main research institutions. International Journal of Molecular Sciences is the most popular journal in this field, while Stem Cell Research & Therapy is the most frequently cited journal. These papers come from 7546 authors, among which Zhang Wei has published the most papers and Zhang Bin has the most cocited papers. The research on the treatment strategy of extracellular vesicles in the process of wound healing is the main topic in this field. "exosomes", "miRNA", "angiogenesis", "regenerative medicine", "inflammation" and "diabetic wound" are the main key words of emerging research hotspots. This is the first bibliometric study, which comprehensively summarises the research trend and development of extracellular vesicles and exocrine bodies in wound healing. These informations determine the latest research frontiers and hot directions, and provide reference for the study of extracellular vesicles and exosomes. [ABSTRACT FROM AUTHOR]

In line with recent proposals for experimental philosophy and philosophy of science in practice, we propose that the philosophy of medicine could benefit from incorporating empirical research, just as bioethics has. In this paper, we therefore take first steps towards the development of an empirical philosophy of medicine, that includes investigating practical and moral dimensions. This qualitative study gives insight into the views and experiences of a group of various medical professionals and patient representatives regarding the conceptualization of health and disease concepts in practice and the possible problems that surround them. This includes clinical, epistemological, and ethical issues. We have conducted qualitative interviews with a broad range of participants (n = 17), working in various health-related disciplines, fields and organizations. From the interviews, we highlight several different practical functions of definitions of health and disease. Furthermore, we discuss 5 types of problematic situations that emerged from the interviews and analyze the underlying conceptual issues. By providing theoretical frameworks and conceptual tools, and by suggesting conceptual changes or adaptations, philosophers might be able to help solve some of these problems. This empirical-philosophical study contributes to a more pragmatic way of understanding the relevance of conceptualizing health and disease by connecting the participants' views and experiences to the theoretical debate. Going back and forth between theory and practice will likely result in a more complex but hopefully also better and more fruitful understanding of health and disease concepts. [ABSTRACT FROM AUTHOR]

Copyright of Revista de Medicina y Cine / Journal of Medicine & Movies is the property of Ediciones Universidad de Salamanca and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

The paper describes quantitative and qualitative dimensions of nanomedicine research studies in India. The study is based on research publications data in nanomedicine research (1491 publications) as covered in Scopus data base for the period 2002-20. The study finds that nanomedicine research in India registered a high 73.7% growth with an average of 22.93 citations per paper. The nano-oncology subfield accounted for the highest share (48.49% share) in the national output, followed by seven other nanomedicine subfields. Jamia Hamdard University, Delhi, Panjab University, Chandigarh and Banaras Hindu University, Varanasi lead as the most productive organizations in the country. The paper also lists the most productive authors in nanomedicine research. The most productive research journals that reported nanomedicine research in India include Nanomedicine, International Journal of Nanomedicine and Current Pharmaceutical Design. In addition, International Journal of Pharmaceutics, International Journal of Nanomedicine and Drug Delivery Today topped in the list of most cited research journals. [ABSTRACT FROM AUTHOR]

Effective communication in medical writing is essential for conveying accurate and understandable information to healthcare professionals and patients. English language errors in medical literature can lead to misunderstandings, misinterpretations, and potentially harmful consequences. This systematic literature review aims to identify, analyze, and categorize common English language errors encountered in medical writing. This study identifies gaps in existing literature on language errors in medical writing and reveals areas that need further investigation or where more comprehensive guidelines are required. This study addresses six questions: (1) What types of language errors are discussed in the current literature? (2) What types of medical writing are involved in the current literature? (3) Which countries or areas are involved in the current literature? (4) What are the research methods used in the studies? (5) What tools are used in the studies? (6) What are the limitations of these studies? To answer these questions, this review searched nine databases and one platform, ProQuest Dissertations and Theses Fulltext, ProQuest Ebook Central (e-Books), Scopus, Web of Science, Wiley Online Library (e-Journals & e-Books) (PPV), Science Direct, Cambridge Core e-Books, Oxford Press Scholarship Online (e-Books), Google Scholar, and Carian Bestari@UKM / Discovery Service@UKM. Finally, ten studies were selected, including articles and books. The findings provide insights into types of language errors, types of medical writing, countries or areas of medical writing, research methods, tools, and limitations of these ten studies, highlighting the importance of linguistic accuracy and proficiency in medical writing. [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]

With the swift pace of the development of artificial intelligence (AI) in diverse spheres, the medical and healthcare fields are utilizing machine learning (ML) methodologies in numerous inventive ways. ML techniques have outstripped formerly state-of-the-art techniques in medical and healthcare practices, yielding faster and more precise outcomes. Healthcare practitioners are increasingly drawn to this technology in their initiatives relating to the Internet of Behavior (IoB). This area of research scrutinizes the rationales, approaches, and timing of human technology adoption, encompassing the domains of the Internet of Things (IoT), behavioral science, and edge analytics. The significance of ML in medical and healthcare applications based on the IoB stems from its ability to analyze and interpret copious amounts of complex data instantly, providing innovative perspectives that can enhance healthcare outcomes and boost the efficiency of IoB-based medical and healthcare procedures and thus aid in diagnoses, treatment protocols, and clinical decision making. As a result of the inadequacy of thorough inquiry into the employment of ML-based approaches in the context of using IoB for healthcare applications, we conducted a study on this subject matter, introducing a novel taxonomy that underscores the need to employ each ML method distinctively. With this objective in mind, we have classified the cutting-edge ML solutions for IoB-based healthcare challenges into five categories, which are convolutional neural networks (CNNs), recurrent neural networks (RNNs), deep neural networks (DNNs), multilayer perceptions (MLPs), and hybrid methods. In order to delve deeper, we conducted a systematic literature review (SLR) that examined critical factors, such as the primary concept, benefits, drawbacks, simulation environment, and datasets. Subsequently, we highlighted pioneering studies on ML methodologies for IoB-based medical issues. Moreover, several challenges related to the implementation of ML in healthcare and medicine have been tackled, thereby gradually fostering further research endeavors that can enhance IoB-based health and medical studies. Our findings indicated that Tensorflow was the most commonly utilized simulation setting, accounting for 24% of the proposed methodologies by researchers. Additionally, accuracy was deemed to be the most crucial parameter in the majority of the examined papers. [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]

Copyright of Clotho is the property of University of Ljubljana, Faculty of the Arts and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Imagery is an overarching feature of Maximus of Tyre's Orations which has never been the subject of systematic investigation. This paper provides a starting point by focusing exclusively on medical imagery, one of the most pervasive and instrumental types of imagery in Maximus' work that has gone entirely unnoticed in the literature to date. This paper shows that Maximus uses medicine (especially its scientific basis and historical development), the physician (e.g. his skill, provision and sensitivity towards the patient), the body (its physiology and workings) and notions of health and disease with considerable diversity and creativity, in ways that make his examples stand out in relation to earlier (Platonic) or contemporary applications of the medical parallel. It argues that the use of the medical imagery in the pedagogical context in which Maximus' Orations were performed facilitated not just clarity but also concept formation and the shaping of a moral outlook as well as the familiarisation with the proper literary references and verbal and conceptual topoi for admission into the group of the educated elite. Another main thesis is that medical imagery valorises Maximus' philosophical status and his claims to Imperial-period acculturation, thus functioning as a trademark for the rhetorical philosophy he wished to promote. [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]

Many of the artificial intelligence (AI) systems used nowadays have a very high level of accuracy but fail to explain their decisions. This is critical, especially in sensitive areas such as medicine and the health area at large but also for applications of the law, finance etc., where explanations for certain decisions are needed and are often useful and valuable as the decision itself. This paper presents a review of four different methods for creating transparency in AI systems. It also suggests a list of criteria under which circumstances one should use which methods. [ABSTRACT FROM AUTHOR]

Copyright of Revista de Medicina y Cine / Journal of Medicine & Movies is the property of Ediciones Universidad de Salamanca and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

The aim of this systematic review is to describe and identify the prospects of β-Tricalcium Phosphate (β-TCP) as an alveolar bone grafting (ABG) material in cleft lip/palate (CL/P) or alveolar bone cleft defects. A systematic review protocol based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 (PRISMA 2020) was drafted. The literature search was conducted using MEDLINE/PubMed, Web of Science/ISI Web of Knowledge, Scopus, and the Cochrane Library, with English as the inclusion criterion and no publication year limits. The keywords yielded a total of 5824 publications. After removing duplicates and non-English articles, there were 3196 suitable articles available for evaluation. Subsequently, 1315 studies remained after reviewing titles and abstracts. Furthermore, 85 full articles were assessed for eligibility. After reading the complete texts of those papers, 20 were eventually selected that matched the inclusion requirements. Thirteen out of the twenty studies included in this systematic review were deemed to have a low risk of bias; one had a high risk of bias; and six had a moderate risk of bias due to not reporting randomization. β-TCP, when used as an ABG material, is biocompatible, visible, practical, offers a less invasive procedure, and does not interfere with orthodontic treatment. Synthetic β-TCP for ABG can be an alternative to autologous bone grafts under certain terms and conditions. The efficacy of β-TCP for ABG in CL/P or alveolar bone cleft defects can be enhanced through a tissue engineering approach that combines β-TCP with growth factors, mesenchymal stem cells, or other graft materials, along with modifications to β-TCP's physical properties. [ABSTRACT FROM AUTHOR]

In this paper I will develop a gender critique of scientific and medical idealizations of the human body and its health, which was performed out of gender and feminist studies, pointing also to women's art. In the discourses of medicine, healthy and beautiful human - and especially the female human - body is revealed as an ideological construction, an affective agent and a biopolitical ideal that controls and regulates gender differences. My intention is to demonstrate that the discourses of medicine, feminism, and art are in a dialogue historically in relation to these topics. Following Tasha N. Dubriwny's discussion of medical discourse and practice, I will map three phases in the development of Western medical discourses and point to the fact that they are in dialogue with feminist discourses and with the way how art treats and represents beautiful bodies, and/or sick bodies, with particular focus on female bodies. Discussion of the first phase of medical development points to the fact that visual art and photography were used to performatively help doctors to construct the female body as sick and deviant, as Didi Huberman showed. The second phase was the medicalization era, in which human bodies are expected to adhere to a standardized norm. In this period, within the framework of second wave feminism, feminist health activists appeared, forming the women's movement for health. Special attention will be directed to the third phase, the biomedicalization era or inclusion-and-difference paradigm, in which postfeminist discourses appeared and in relation to which I will discuss artworks by Hannah Wilke, Katarzyna Kozyra, and Orlan. [ABSTRACT FROM AUTHOR]

This paper discusses the objective reasons for the growing need for qualified medical services, especially in the context of pandemics, wars, disasters, and shortages of medical staff. The directions of development of robotics in medicine are analyzed, leading to the conclusion that the use of intelligent collaborative (i.e., interacting with humans) robotics in medicine is possible and appropriate. Robot assistants can perform many auxiliary operations, which will help relieve the workload of middle and junior medical staff, and, if necessary, replace them when performing such operations. The article outlines some of the main directions in which the authors believe the development of collaborative medical robotics should occur. [ABSTRACT FROM AUTHOR]

Nowadays, entomology is one of the most studied domains due to the pivotal role of insects in ecology, agriculture, the pharmaceutical industry, and medicine. Insects are the most diverse and numerous group of species, and their impact represents a high interest for the scientific community. Due to their well-documented high applicability in various areas, two of the most studied insects are silkworms and honeybees. One of the most important roles of silkworms is their role in medicine and the pharmaceutic industry as bioreactors and model organisms. Honeybees represent the main pollinator for numerous crops and wild plants and present a major contribution to the food chain. Despite their beneficial role in nature and the numerous products obtained from the hive, the bees face several stressors, both biotic and abiotic. The most important progress in this direction has been made by applying genome editing tools to enhance their productivity and agricultural sustainability. Until now, researchers have obtained disease-resistant individuals, limiting the high need for chemical treatments and promoting environmental health. These advancements exhibit progress in biotechnological innovations, including the production of innovative biomaterials for medical applications, underscoring the broad impact of these techniques on the economy, ecology, and medicine. [ABSTRACT FROM AUTHOR]

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Diagnosis with a brain tumor is a critical event in the lives of patients and their families due to poor medical prognoses and complex clinical care. Spiritual care interventions have been known to have meaningful effects in morbid diagnoses and palliative medicine, but their role in the neuro-oncologic patient's experience is poorly understood. This systematic review explores the role of spirituality and its relevance to patient care in the diverse setting of brain tumors. Methods: A comprehensive systematic review was conducted following PRISMA-SR guidelines. PUBMED was queried for studies on spirituality and neuro-oncology. Identified studies included RCTs, interviews, surveys, and case reports that examined spirituality in neuro-oncological clinical care, quality of life, and patient experience. Of 214 articles identified, 21 studies met the inclusion criteria, and the results were narratively synthesized. Results: Spirituality may play a significant role in mental well-being by reconciling existential questions faced by both patients and caregivers, and can serve as a valuable resource to improve mental well-being and reduce rates of palliative caregiver burnout. However, the paucity of studies examining the education and integration of spiritual awareness within the clinical literature warrants further study. Conclusions: While spiritual care interventions may improve the quality of life and mental wellness of patients and their caregivers, it is unclear how spiritual awareness and education should best be implemented. Further research is needed to better understand how key components of spiritual awareness can be integrated into medical education to deepen the patient–physician relationship and improve clinical experiences. [ABSTRACT FROM AUTHOR]

Meditation, psychedelics, and other similar practices or induction methods that can modulate conscious experience, are becoming increasingly popular in clinical and non-clinical settings. The phenomenology associated with such practices or modalities is vast. Many similar effects and experiences are also reported to occur spontaneously. We argue that this experiential range is still not fully described or understood in the contemporary literature, and that there is an ethical mandate to research it more extensively, starting with comprehensive documentation and definition. We review 50 recent clinical or scientific publications to assess the range of phenomena, experiences, effects, after-effects, and impacts associated with a broad variety of psychoactive compounds, meditative practices, and other modalities or events. This results in a large inventory synthesizing the reports of over 30,000 individual subjects. We then critically discuss various terms and concepts that have been used in recent literature to designate all or parts of the range this inventory covers. We make the case that specialized terminologies are needed to ground the nascent research field that is forming around this experiential domain. As a step in this direction, we propose the notion of “emergence” and some of its derivatives, such as “emergent phenomenology,” as possibly foundational candidates. [ABSTRACT FROM AUTHOR]

The adoption of machine learning (ML) and, more specifically, deep learning (DL) applications into all major areas of our lives is underway. The development of trustworthy AI is especially important in medicine due to the large implications for patients' lives. While trustworthiness concerns various aspects including ethical, transparency and safety requirements, we focus on the importance of data quality (training/test) in DL. Since data quality dictates the behaviour of ML products, evaluating data quality will play a key part in the regulatory approval of medical ML products. We perform a systematic review following PRISMA guidelines using the databases Web of Science, PubMed and ACM Digital Library. We identify 5408 studies, out of which 120 records fulfil our eligibility criteria. From this literature, we synthesise the existing knowledge on data quality frameworks and combine it with the perspective of ML applications in medicine. As a result, we propose the METRIC-framework, a specialised data quality framework for medical training data comprising 15 awareness dimensions, along which developers of medical ML applications should investigate the content of a dataset. This knowledge helps to reduce biases as a major source of unfairness, increase robustness, facilitate interpretability and thus lays the foundation for trustworthy AI in medicine. The METRIC-framework may serve as a base for systematically assessing training datasets, establishing reference datasets, and designing test datasets which has the potential to accelerate the approval of medical ML products. [ABSTRACT FROM AUTHOR]

We discuss the concept of a 'body', the individual body as the lived experience of the body, the social body, shaped by the tensions between the demands of a social/moral order and the egocentric drives, and the body politic, as an institutionalized and disciplined body. We describe the body as it was perceived in Classical Greek Antiquity at the time when the Hippocratic Oath was first conceived, and any changes that may have occurred by Late Antiquity, using the concept of a body-world as represented by everyday life, the arts, politics, philosophy, and religion. This 'recreated' body-world elucidates how a person of Classical or Late Antiquity perceived her/his body via their 'lived-in' world and relates it to medical and philosophical thinking about the body as well as to concepts of health and disease. We demonstrate how the institutional structures of the Roman Empire and the Church influenced the way a body was understood, how the administrative and governmental needs led to the first developments of Public Health, and how the Christian understanding of the body as the body and spirit of Christ changed the attitude towards suicide, euthanasia, and abortion. These changes are reflected in the understanding of bioethical thinking and affected the interpretation of the Hippocratic Oath. [ABSTRACT FROM AUTHOR]

Despite pronouncements about the inevitable diffusion of artificial intelligence and autonomous technologies, in practice, it is human behavior, not technology in a vacuum, that dictates how technology seeps into—and changes—societies. To better understand how human preferences shape technological adoption and the spread of AI-enabled autonomous technologies, we look at representative adult samples of US public opinion in 2018 and 2020 on the use of four types of autonomous technologies: vehicles, surgery, weapons, and cyber defense. By focusing on these four diverse uses of AI-enabled autonomy that span transportation, medicine, and national security, we exploit the inherent variation between these AI-enabled autonomous use cases. We find that those with familiarity and expertise with AI and similar technologies were more likely to support all of the autonomous applications we tested (except weapons) than those with a limited understanding of the technology. Individuals that had already delegated the act of driving using ride-share apps were also more positive about autonomous vehicles. However, familiarity cut both ways; individuals are also less likely to support AI-enabled technologies when applied directly to their life, especially if technology automates tasks they are already familiar with operating. Finally, we find that familiarity plays little role in support for AI-enabled military applications, for which opposition has slightly increased over time. [ABSTRACT FROM AUTHOR]

Background: Food–drug interactions (FDIs) may alter drug pharmacokinetics and pharmacodynamics, modifying the whole therapy's effectiveness. Some of them cause the attenuation of drug effects, while others inhibit the medicines' metabolism resulting, in too high concentrations of the medicine in the body. Thus, some healthcare professionals—doctors, pharmacists or dieticians—should be aware of the possibility of food–drug interactions. This study aimed to assess knowledge of food–drug interactions among students of pharmacy, medicine, stomatology, medical analysis and dietetics and students of the college of further medical education for pharmacy technicians. Methods: Students (n = 820) completed a custom-made questionnaire. The relationships between the continuous variables were analysed on the basis of Pearson's correlation coefficient. To verify the predictors of objective students' knowledge about food–drug interactions, a multiple linear regression model with analysis of covariance (ANCOVA) was used. The Kruskal–Wallis test was performed to compare the total scores the respondents received for questions assessing their objective knowledge of FDI. Results: Students' objective knowledge of FDIs correlated positively with their year of study and their self-evaluation of it. It was also significantly influenced by the field and mode of studies and by the fact that the issue had been discussed during the courses. Conclusions: Most students of the medical university had serious deficiencies in their knowledge of food–drug interactions. This is of particular concern for future doctors and dentists. Among the respondents, pharmacy students stood out, as their FDI knowledge was greater. The issue of food–drug interactions should be more widely taught at medical universities, which was emphasised by the respondents themselves. [ABSTRACT FROM AUTHOR]

Depression is a multifactorial disease with unknown etiology affecting globally. It's the second most significant reason for infirmity in 2020, affecting about 50 million people worldwide, with 80% living in developing nations. Recently, a surge in depression research has been witnessed, resulting in a multitude of emerging techniques developed for prediction, evaluation, detection, classification, localization, and treatment. The main purpose of this study is to determine the volume of depression research conducted on different aspects such as genetics, proteins, hormones, oxidative stress, inflammation, mitochondrial dysfunction, and associations with other mental disorders like anxiety and stress using traditional and medical intelligence (medical with AI). In addition, it also designs a comprehensive survey on detection, treatment planning, and genetic predisposition, along with future recommendations. This work is designed through different methods, including a systematic mapping process, literature review, and network visualization. In addition, we also used VOSviewer software and some authentic databases such as Google Scholar, Scopus, PubMed, and Web of Science for data collection, analysis, and designing comprehensive picture of the study. We analyzed 60 articles related to medical intelligence, including 47 from machine learning with 513,767 subjects (mean ± SD = 10,931.212 ± 35,624.372) and 13 from deep learning with 37,917 subjects (mean ± SD = 3159.75 ± 6285.57). Additionally, we also found that stressors impact the brain's cognitive and autonomic functioning, resulting in increased production of catecholamine, decreased cholinergic and glucocorticoid activity, with increased cortisol. These factors lead to chronic inflammation and hinder the brain's normal functioning, leading to depression, anxiety, and cardiovascular disorders. In the brain, reactive oxygen species (ROS) production is increased by IL-6 stimulation and mitochondrial cytochrome c oxidase is inhibited by nitric oxide, a potent inhibitor. Proteins, lipids, oxidative phosphorylation enzymes, and mtDNA are further disposed to oxidative impairment in the mitochondria. Consequently, mitochondrial dysfunction exacerbates oxidative stress, impairs mitochondrial DNA (mtDNA) or deletions of mtDNA, increases intracellular Ca2+ levels, changes in fission/fusion and mitochondrial morphology, and lastly leads to neuronal death. This study highlights the multidisciplinary approaches to depression with different aspects using traditional and medical intelligence. It will open a new way for depression research through new emerging technologies. [ABSTRACT FROM AUTHOR]

Background: Depression, anxiety, and insomnia are prevalent in older people and are associated with increased risk of mortality, dependency, falls and reduced quality of life. Prior to or whilst seeking treatment, older people often manage these symptoms or conditions using products purchased over the counter (OTC), such as medication or herbal products. This review aims to map the evidence available for OTC medications, herbal medicines and dietary supplements for depression, anxiety and insomnia in older adults. Methodology: We carried out a scoping review, including searches of five databases to identify relevant randomised controlled trials (inception-Dec 2022). We took an inclusive approach to products to represent the wide range that may be available online. Trials were summarised according to condition and product. Results: We included 47 trials and 10 ongoing trial protocols. Most targeted insomnia (n = 25), followed by depression (n = 20), and mixed conditions (n = 2). None evaluated products targeted at anxiety alone. Where reported, most products appeared to be safe for use, but studies rarely included people with multiple comorbidities or taking concomitant medication. Some types of melatonin for insomnia (n = 19) and omega-3 fatty acids for depression (n = 7) had more substantive evidence compared to the other products. Conclusion: There is a substantial gap in evidence for OTC products for anxiety in older people. This should be addressed in future trials. Research should also focus on products that are widely used, and these need to be tested in older populations that are similar to those who would use them in practice. Key points: We carried out a scoping review of over-the-counter products for depression, anxiety and insomnia in older people. Out of 47 trials and 10 ongoing protocols, most studies targeted depression or insomnia - none targeted anxiety alone. Few products had more than one trial available, apart from melatonin and omega-3s, and studies rarely included people with multiple comorbidities or taking concomitant medication. [ABSTRACT FROM AUTHOR]