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37352529 | ChatGPT encounters multiple opportunities and challenges in neurosurgery. | 2,023 | International journal of surgery (London, England) | BACKGROUND: ChatGPT, powered by the GPT model and Transformer architecture, has demonstrated remarkable performance in the domains of medicine and healthcare, providing customized and informative responses. In our study, we investigated the potential of ChatGPT in the field of neurosurgery, focusing on its applications... | Kuang YR; Zou MX; Niu HQ; Zheng BY; Zhang TL; Zheng BW | 0-1 | |||
37389908 | Reliability of Medical Information Provided by ChatGPT: Assessment Against Clinical Guidelines and Patient Information Quality Instrument. | 2,023 | Journal of medical Internet research | BACKGROUND: ChatGPT-4 is the latest release of a novel artificial intelligence (AI) chatbot able to answer freely formulated and complex questions. In the near future, ChatGPT could become the new standard for health care professionals and patients to access medical information. However, little is known about the quali... | Walker HL; Ghani S; Kuemmerli C; Nebiker CA; Muller BP; Raptis DA; Staubli SM | 43 | |||
38465158 | Enhancing Postoperative Cochlear Implant Care With ChatGPT-4: A Study on Artificial Intelligence (AI)-Assisted Patient Education and Support. | 2,024 | Cureus | BACKGROUND: Cochlear implantation is a critical surgical intervention for patients with severe hearing loss. Postoperative care is essential for successful rehabilitation, yet access to timely medical advice can be challenging, especially in remote or resource-limited settings. Integrating advanced artificial intellige... | Aliyeva A; Sari E; Alaskarov E; Nasirov R | 32 | |||
38420978 | Performance of ChatGPT in Israeli Hebrew Internal Medicine National Residency Exam. | 2,024 | The Israel Medical Association journal : IMAJ | BACKGROUND: Completing internal medicine specialty training in Israel involves passing the Israel National Internal Medicine Exam (Shlav Aleph), a challenging multiple-choice test. multiple-choice test. Chat generative pre-trained transformer (ChatGPT) 3.5, a language model, is increasingly used for exam preparation. O... | Ozeri DJ; Cohen A; Bacharach N; Ukashi O; Oppenheim A | 21 | |||
39911377 | Evaluation of GPT-4 concordance with north American spine society guidelines for lumbar fusion surgery. | 2,025 | North American Spine Society journal | BACKGROUND: Concordance with evidence-based medicine (EBM) guidelines is associated with improved clinical outcomes in spine surgery. The North American Spine Society (NASS) has published coverage guidelines on indications for lumbar fusion surgery, with a recent survey demonstrating a 60% concordance rate across its m... | Khoylyan A; Salvato J; Vazquez F; Girgis M; Tang A; Chen T | 32 | |||
40059391 | The Need to Improve the Medical Subject Headings (MeSH) and the Excerpta Medica Tree (EMTREE) Thesauri to Perform Systematic Review on Oral Potentially Malignant Disorders. | 2,025 | Journal of oral pathology & medicine : official publication of the International Association of Oral Pathologists and the American Academy of Oral Pathology | BACKGROUND: Despite recent advancements in the understanding and classification of oral potentially malignant disorders (OPMD), their terminology remains inconsistent and heterogeneous throughout the scientific literature, thus affecting evidence-based decision-making relevant for clinical management of these disorders... | Caponio VCA; Musella G; Perez-Sayans M; Lo Muzio L; Amaral Mendes R; Lopez-Pintor RM | 0-1 | |||
39941547 | Performance of ChatGPT in Pediatric Audiology as Rated by Students and Experts. | 2,025 | Journal of clinical medicine | Background: Despite the growing popularity of artificial intelligence (AI)-based systems such as ChatGPT, there is still little evidence of their effectiveness in audiology, particularly in pediatric audiology. The present study aimed to verify the performance of ChatGPT in this field, as assessed by both students and ... | Ratuszniak A; Gos E; Lorens A; Skarzynski PH; Skarzynski H; Jedrzejczak WW | 32 | |||
37128784 | Performance of ChatGPT on the Plastic Surgery Inservice Training Examination. | 2,023 | Aesthetic surgery journal | BACKGROUND: Developed originally as a tool for resident self-evaluation, the Plastic Surgery Inservice Training Examination (PSITE) has become a standardized tool adopted by Plastic Surgery residency programs. The introduction of large language models (LLMs), such as ChatGPT (OpenAI, San Francisco, CA), has demonstrate... | Gupta R; Herzog I; Park JB; Weisberger J; Firouzbakht P; Ocon V; Chao J; Lee ES; Mailey BA | 32 | |||
39148849 | Foundational model aided automatic high-throughput drug screening using self-controlled cohort study. | 2,024 | medRxiv : the preprint server for health sciences | BACKGROUND: Developing medicine from scratch to governmental authorization and detecting adverse drug reactions (ADR) have barely been economical, expeditious, and risk-averse investments. The availability of large-scale observational healthcare databases and the popularity of large language models offer an unparallele... | Xu S; Cobzaru R; Finkelstein SN; Welsch RE; Ng K; Middleton L | 10 | |||
39229463 | Diagnostic performance of generative artificial intelligences for a series of complex case reports. | 2,024 | Digital health | BACKGROUND: Diagnostic performance of generative artificial intelligences (AIs) using large language models (LLMs) across comprehensive medical specialties is still unknown. OBJECTIVE: We aimed to evaluate the diagnostic performance of generative AIs using LLMs in complex case series across comprehensive medical fields... | Hirosawa T; Harada Y; Mizuta K; Sakamoto T; Tokumasu K; Shimizu T | 10 | |||
39094112 | Patient-Representing Population's Perceptions of GPT-Generated Versus Standard Emergency Department Discharge Instructions: Randomized Blind Survey Assessment. | 2,024 | Journal of medical Internet research | BACKGROUND: Discharge instructions are a key form of documentation and patient communication in the time of transition from the emergency department (ED) to home. Discharge instructions are time-consuming and often underprioritized, especially in the ED, leading to discharge delays and possibly impersonal patient instr... | Huang T; Safranek C; Socrates V; Chartash D; Wright D; Dilip M; Sangal RB; Taylor RA | 10 | |||
40385316 | Can large language models detect drug-drug interactions leading to adverse drug reactions? | 2,025 | Therapeutic advances in drug safety | BACKGROUND: Drug-drug interactions (DDI) are an important cause of adverse drug reactions (ADRs). Could large language models (LLMs) serve as valuable tools for pharmacovigilance specialists in detecting DDIs that lead to ADR notifications? OBJECTIVE: To compare the performance of three LLMs (ChatGPT, Gemini, and Claud... | Sicard J; Montastruc F; Achalme C; Jonville-Bera AP; Songue P; Babin M; Soeiro T; Schiro P; de Canecaude C; Barus R | 10 | |||
39702867 | Aligning Large Language Models with Humans: A Comprehensive Survey of ChatGPT's Aptitude in Pharmacology. | 2,025 | Drugs | BACKGROUND: Due to the lack of a comprehensive pharmacology test set, evaluating the potential and value of large language models (LLMs) in pharmacology is complex and challenging. AIMS: This study aims to provide a test set reference for assessing the application potential of both general-purpose and specialized LLMs ... | Zhang Y; Ren S; Wang J; Lu J; Wu C; He M; Liu X; Wu R; Zhao J; Zhan C; Du D; Zhan Z; Singla RK; Shen B | 10 | |||
39507462 | Artificial intelligence generates proficient Spanish obstetrics and gynecology counseling templates. | 2,024 | AJOG global reports | BACKGROUND: Effective patient counseling in Obstetrics and gynecology is vital. Existing language barriers between Spanish-speaking patients and English-speaking providers may negatively impact patient understanding and adherence to medical recommendations, as language discordance between provider and patient has been ... | Solmonovich RL; Kouba I; Quezada O; Rodriguez-Ayala G; Rojas V; Bonilla K; Espino K; Bracero LA | 0-1 | |||
38819879 | Redefining Health Care Data Interoperability: Empirical Exploration of Large Language Models in Information Exchange. | 2,024 | Journal of medical Internet research | BACKGROUND: Efficient data exchange and health care interoperability are impeded by medical records often being in nonstandardized or unstructured natural language format. Advanced language models, such as large language models (LLMs), may help overcome current challenges in information exchange. OBJECTIVE: This study ... | Yoon D; Han C; Kim DW; Kim S; Bae S; Ryu JA; Choi Y | 10 | |||
40374171 | Patient Triage and Guidance in Emergency Departments Using Large Language Models: Multimetric Study. | 2,025 | Journal of medical Internet research | BACKGROUND: Emergency departments (EDs) face significant challenges due to overcrowding, prolonged waiting times, and staff shortages, leading to increased strain on health care systems. Efficient triage systems and accurate departmental guidance are critical for alleviating these pressures. Recent advancements in larg... | Wang C; Wang F; Li S; Ren QW; Tan X; Fu Y; Liu D; Qian G; Cao Y; Yin R; Li K | 10 | |||
38432929 | Performance of a Large Language Model on Japanese Emergency Medicine Board Certification Examinations. | 2,024 | Journal of Nippon Medical School = Nippon Ika Daigaku zasshi | BACKGROUND: Emergency physicians need a broad range of knowledge and skills to address critical medical, traumatic, and environmental conditions. Artificial intelligence (AI), including large language models (LLMs), has potential applications in healthcare settings; however, the performance of LLMs in emergency medicin... | Igarashi Y; Nakahara K; Norii T; Miyake N; Tagami T; Yokobori S | 21 | |||
39137031 | Educational Utility of Clinical Vignettes Generated in Japanese by ChatGPT-4: Mixed Methods Study. | 2,024 | JMIR medical education | BACKGROUND: Evaluating the accuracy and educational utility of artificial intelligence-generated medical cases, especially those produced by large language models such as ChatGPT-4 (developed by OpenAI), is crucial yet underexplored. OBJECTIVE: This study aimed to assess the educational utility of ChatGPT-4-generated c... | Takahashi H; Shikino K; Kondo T; Komori A; Yamada Y; Saita M; Naito T | 0-1 | |||
39823287 | Performance of ChatGPT-4o in the diagnostic workup of fever among returning travellers requiring hospitalization: a validation study. | 2,025 | Journal of travel medicine | BACKGROUND: Febrile illness in returned travellers presents a diagnostic challenge in non-endemic settings. Chat generative pretrained transformer (ChatGPT) has the potential to assist in medical tasks, yet its diagnostic performance in clinical settings has rarely been evaluated. We conducted a validation assessment o... | Yelin D; Shirin N; Harris I; Peretz Y; Yahav D; Schwartz E; Leshem E; Margalit I | 10 | |||
39974103 | The Clinical Value of ChatGPT for Epilepsy Presurgical Decision Making: Systematic Evaluation on Seizure Semiology Interpretation. | 2,025 | medRxiv : the preprint server for health sciences | BACKGROUND: For patients with drug-resistant focal epilepsy (DRE), surgical resection of the epileptogenic zone (EZ) is an effective treatment to control seizures. Accurate localization of the EZ is crucial and is typically achieved through comprehensive presurgical approaches such as seizure semiology interpretation, ... | Luo Y; Jiao M; Fotedar N; Ding JE; Karakis I; Rao VR; Asmar M; Xian X; Aboud O; Wen Y; Lin JJ; Hung FM; Sun H; Rosenow F; Liu F | 10 | |||
40354107 | Clinical Value of ChatGPT for Epilepsy Presurgical Decision-Making: Systematic Evaluation of Seizure Semiology Interpretation. | 2,025 | Journal of medical Internet research | BACKGROUND: For patients with drug-resistant focal epilepsy, surgical resection of the epileptogenic zone (EZ) is an effective treatment to control seizures. Accurate localization of the EZ is crucial and is typically achieved through comprehensive presurgical approaches such as seizure semiology interpretation, electr... | Luo Y; Jiao M; Fotedar N; Ding JE; Karakis I; Rao VR; Asmar M; Xian X; Aboud O; Wen Y; Lin JJ; Hung FM; Sun H; Rosenow F; Liu F | 10 | |||
39427271 | Chasing sleep physicians: ChatGPT-4o on the interpretation of polysomnographic results. | 2,025 | European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery | BACKGROUND: From a healthcare professional's perspective, the use of ChatGPT (Open AI), a large language model (LLM), offers huge potential as a practical and economic digital assistant. However, ChatGPT has not yet been evaluated for the interpretation of polysomnographic results in patients with suspected obstructive... | Seifen C; Huppertz T; Gouveris H; Bahr-Hamm K; Pordzik J; Eckrich J; Smith H; Kelsey T; Blaikie A; Matthias C; Kuhn S; Buhr CR | 0-1 | |||
38185435 | A review of top cardiology and cardiovascular medicine journal guidelines regarding the use of generative artificial intelligence tools in scientific writing. | 2,024 | Current problems in cardiology | BACKGROUND: Generative Artificial Intelligence (AI) tools have experienced rapid development over the last decade and are gaining increasing popularity as assistive models in academic writing. However, the ability of AI to generate reliable and accurate research articles is a topic of debate. Major scientific journals ... | Inam M; Sheikh S; Minhas AMK; Vaughan EM; Krittanawong C; Samad Z; Lavie CJ; Khoja A; D'Cruze M; Slipczuk L; Alarakhiya F; Naseem A; Haider AH; Virani SS | 10 | |||
38446539 | Leveraging Generative AI Tools to Support the Development of Digital Solutions in Health Care Research: Case Study. | 2,024 | JMIR human factors | BACKGROUND: Generative artificial intelligence has the potential to revolutionize health technology product development by improving coding quality, efficiency, documentation, quality assessment and review, and troubleshooting. OBJECTIVE: This paper explores the application of a commercially available generative artifi... | Rodriguez DV; Lawrence K; Gonzalez J; Brandfield-Harvey B; Xu L; Tasneem S; Levine DL; Mann D | 0-1 | |||
39948214 | Evaluation of the Performance of Three Large Language Models in Clinical Decision Support: A Comparative Study Based on Actual Cases. | 2,025 | Journal of medical systems | BACKGROUND: Generative large language models (LLMs) are increasingly integrated into the medical field. However, their actual efficacy in clinical decision-making remains partially unexplored. This study aimed to assess the performance of the three LLMs, ChatGPT-4, Gemini, and Med-Go, in the domain of professional medi... | Wang X; Ye H; Zhang S; Yang M; Wang X | 10 | |||
39396402 | PresRecRF: Herbal prescription recommendation via the representation fusion of large TCM semantics and molecular knowledge. | 2,024 | Phytomedicine : international journal of phytotherapy and phytopharmacology | BACKGROUND: Herbal prescription recommendation (HPR) is a hotspot in the research of clinical intelligent decision support. Recently plentiful HPR models based on deep neural networks have been proposed. Owing to insufficient data, e.g., lack of knowledge of molecular, TCM theory, and herbal dosage in HPR modeling, the... | Yang K; Dong X; Zhang S; Yu H; Zhong L; Zhang L; Zhao H; Hou Y; Song X; Zhou X | 10 | |||
39718328 | Artificial Intelligence, the ChatGPT Large Language Model: Assessing the Accuracy of Responses to the Gynaecological Endoscopic Surgical Education and Assessment (GESEA) Level 1-2 knowledge tests. | 2,024 | Facts, views & vision in ObGyn | BACKGROUND: In 2022, OpenAI launched ChatGPT 3.5, which is now widely used in medical education, training, and research. Despite its valuable use for the generation of information, concerns persist about its authenticity and accuracy. Its undisclosed information source and outdated dataset pose risks of misinformation.... | Pavone M; Palmieri L; Bizzarri N; Rosati A; Campolo F; Innocenzi C; Taliento C; Restaino S; Catena U; Vizzielli G; Akladios C; Ianieri MM; Marescaux J; Campo R; Fanfani F; Scambia G | 43 | |||
40405178 | Challenging cases of hyponatremia incorrectly interpreted by ChatGPT. | 2,025 | BMC medical education | BACKGROUND: In clinical medicine, the assessment of hyponatremia is frequently required but also known as a source of major diagnostic errors, substantial mismanagement, and iatrogenic morbidity. Because artificial intelligence techniques are efficient in analyzing complex problems, their use may possibly overcome curr... | Berend K; Duits A; Gans ROB | 10 | |||
40013072 | Medication counseling for OTC drugs using customized ChatGPT-4: Comparison with ChatGPT-3.5 and ChatGPT-4o. | 2,025 | Digital health | BACKGROUND: In Japan, consumers can purchase most over-the-counter (OTC) drugs without pharmacist guidance. Recently, generative artificial intelligence (AI) has become increasingly popular. Therefore, medical professionals need to consider the use of generative AI by consumers for medication counseling. We have previo... | Kiyomiya K; Aomori T; Ohtani H | 10 | |||
39754097 | Comparison of AI applications and anesthesiologist's anesthesia method choices. | 2,025 | BMC anesthesiology | BACKGROUND: In medicine, Artificial intelligence has begun to be utilized in nearly every domain, from medical devices to the interpretation of imaging studies. There is still a need for more experience and more studies related to the comprehensive use of AI in medicine. The aim of the present study is to evaluate the ... | Celik E; Turgut MA; Aydogan M; Kilinc M; Toktas I; Akelma H | 0-1 | |||
39099569 | The potential of ChatGPT in medicine: an example analysis of nephrology specialty exams in Poland. | 2,024 | Clinical kidney journal | BACKGROUND: In November 2022, OpenAI released a chatbot named ChatGPT, a product capable of processing natural language to create human-like conversational dialogue. It has generated a lot of interest, including from the scientific community and the medical science community. Recent publications have shown that ChatGPT... | Nicikowski J; Szczepanski M; Miedziaszczyk M; Kudlinski B | 21 | |||
37190006 | May Artificial Intelligence Influence Future Pediatric Research?-The Case of ChatGPT. | 2,023 | Children (Basel, Switzerland) | BACKGROUND: In recent months, there has been growing interest in the potential of artificial intelligence (AI) to revolutionize various aspects of medicine, including research, education, and clinical practice. ChatGPT represents a leading AI language model, with possible unpredictable effects on the quality of future ... | Corsello A; Santangelo A | 10 | |||
39578313 | Leveraging ChatGPT for Enhanced Aesthetic Evaluations in Minimally Invasive Facial Procedures. | 2,025 | Aesthetic plastic surgery | BACKGROUND: In recent years, the application of AI technologies like ChatGPT has gained traction in the field of plastic surgery. AI models can analyze pre- and post-treatment images to offer insights into the effectiveness of cosmetic procedures. This technological advancement enables rapid, objective evaluations that... | Ali R; Cui H | 32 | |||
38838389 | Empowering gynaecologists with Artificial Intelligence: Tailoring surgical solutions for fibroids. | 2,024 | European journal of obstetrics, gynecology, and reproductive biology | BACKGROUND: In recent years, the integration ofArtificial intelligence (AI) into various fields of medicine including Gynaecology, has shown promising potential. Surgical treatment of fibroid is myomectomy if uterine preservation and fertility are the primary aims. AI usage begins with the involvement of LLM (Large Lan... | Sinha R; Raina R; Bag M; Rupa B | 0-1 | |||
38592758 | Evaluating ChatGPT-4's Diagnostic Accuracy: Impact of Visual Data Integration. | 2,024 | JMIR medical informatics | BACKGROUND: In the evolving field of health care, multimodal generative artificial intelligence (AI) systems, such as ChatGPT-4 with vision (ChatGPT-4V), represent a significant advancement, as they integrate visual data with text data. This integration has the potential to revolutionize clinical diagnostics by offerin... | Hirosawa T; Harada Y; Tokumasu K; Ito T; Suzuki T; Shimizu T | 10 | |||
38775367 | Evaluation of ChatGPT as a Tool for Answering Clinical Questions in Pharmacy Practice. | 2,024 | Journal of pharmacy practice | Background: In the healthcare field, there has been a growing interest in using artificial intelligence (AI)-powered tools to assist healthcare professionals, including pharmacists, in their daily tasks. Objectives: To provide commentary and insight into the potential for generative AI language models such as ChatGPT a... | Munir F; Gehres A; Wai D; Song L | 10 | |||
39719573 | Assessing the accuracy and quality of artificial intelligence (AI) chatbot-generated responses in making patient-specific drug-therapy and healthcare-related decisions. | 2,024 | BMC medical informatics and decision making | BACKGROUND: Interactive artificial intelligence tools such as ChatGPT have gained popularity, yet little is known about their reliability as a reference tool for healthcare-related information for healthcare providers and trainees. The objective of this study was to assess the consistency, quality, and accuracy of the ... | Shiferaw MW; Zheng T; Winter A; Mike LA; Chan LN | 43 | |||
38401366 | Assessing question characteristic influences on ChatGPT's performance and response-explanation consistency: Insights from Taiwan's Nursing Licensing Exam. | 2,024 | International journal of nursing studies | BACKGROUND: Investigates the integration of an artificial intelligence tool, specifically ChatGPT, in nursing education, addressing its effectiveness in exam preparation and self-assessment. OBJECTIVE: This study aims to evaluate the performance of ChatGPT, one of the most promising artificial intelligence-driven lingu... | Su MC; Lin LE; Lin LH; Chen YC | 21 | |||
37662036 | The utility of ChatGPT in the assessment of literature on the prevention of migraine: an observational, qualitative study. | 2,023 | Frontiers in neurology | BACKGROUND: It is not known how large language models, such as ChatGPT, can be applied toward the assessment of the efficacy of medications, including in the prevention of migraine, and how it might support those claims with existing medical evidence. METHODS: We queried ChatGPT-3.5 on the efficacy of 47 medications fo... | Moskatel LS; Zhang N | 10 | |||
38348835 | Performance of ChatGPT as an AI-assisted decision support tool in medicine: a proof-of-concept study for interpreting symptoms and management of common cardiac conditions (AMSTELHEART-2). | 2,024 | Acta cardiologica | BACKGROUND: It is thought that ChatGPT, an advanced language model developed by OpenAI, may in the future serve as an AI-assisted decision support tool in medicine. OBJECTIVE: To evaluate the accuracy of ChatGPT's recommendations on medical questions related to common cardiac symptoms or conditions. METHODS: We tested ... | Harskamp RE; De Clercq L | 0-1 | |||
40332991 | Comparing Artificial Intelligence-Generated and Clinician-Created Personalized Self-Management Guidance for Patients With Knee Osteoarthritis: Blinded Observational Study. | 2,025 | Journal of medical Internet research | BACKGROUND: Knee osteoarthritis is a prevalent, chronic musculoskeletal disorder that impairs mobility and quality of life. Personalized patient education aims to improve self-management and adherence; yet, its delivery is often limited by time constraints, clinician workload, and the heterogeneity of patient needs. Re... | Du K; Li A; Zuo QH; Zhang CY; Guo R; Chen P; Du WS; Li SM | 32 | |||
37725411 | Assessment of Resident and AI Chatbot Performance on the University of Toronto Family Medicine Residency Progress Test: Comparative Study. | 2,023 | JMIR medical education | BACKGROUND: Large language model (LLM)-based chatbots are evolving at an unprecedented pace with the release of ChatGPT, specifically GPT-3.5, and its successor, GPT-4. Their capabilities in general-purpose tasks and language generation have advanced to the point of performing excellently on various educational examina... | Huang RS; Lu KJQ; Meaney C; Kemppainen J; Punnett A; Leung FH | 21 | |||
38744501 | Evaluating the diagnostic performance of a large language model-powered chatbot for providing immunohistochemistry recommendations in dermatopathology. | 2,024 | Journal of cutaneous pathology | BACKGROUND: Large language model (LLM)-powered chatbots such as ChatGPT have numerous applications. However, their effectiveness in dermatopathology has not been formally evaluated. Dermatopathological cases often require immunohistochemical workup. Here, we evaluate the performance of a chatbot in providing diagnostic... | McCrary MR; Galambus J; Chen WS | 10 | |||
38717811 | ChatGPT as a Tool for Medical Education and Clinical Decision-Making on the Wards: Case Study. | 2,024 | JMIR formative research | BACKGROUND: Large language models (LLMs) are computational artificial intelligence systems with advanced natural language processing capabilities that have recently been popularized among health care students and educators due to their ability to provide real-time access to a vast amount of medical knowledge. The adopt... | Skryd A; Lawrence K | 10 | |||
39729356 | Large Language Models in Worldwide Medical Exams: Platform Development and Comprehensive Analysis. | 2,024 | Journal of medical Internet research | BACKGROUND: Large language models (LLMs) are increasingly integrated into medical education, with transformative potential for learning and assessment. However, their performance across diverse medical exams globally has remained underexplored. OBJECTIVE: This study aims to introduce MedExamLLM, a comprehensive platfor... | Zong H; Wu R; Cha J; Wang J; Wu E; Li J; Zhou Y; Zhang C; Feng W; Shen B | 21 | |||
39546795 | Examining the Role of Large Language Models in Orthopedics: Systematic Review. | 2,024 | Journal of medical Internet research | BACKGROUND: Large language models (LLMs) can understand natural language and generate corresponding text, images, and even videos based on prompts, which holds great potential in medical scenarios. Orthopedics is a significant branch of medicine, and orthopedic diseases contribute to a significant socioeconomic burden,... | Zhang C; Liu S; Zhou X; Zhou S; Tian Y; Wang S; Xu N; Li W | 32 | |||
38952020 | Data Set and Benchmark (MedGPTEval) to Evaluate Responses From Large Language Models in Medicine: Evaluation Development and Validation. | 2,024 | JMIR medical informatics | BACKGROUND: Large language models (LLMs) have achieved great progress in natural language processing tasks and demonstrated the potential for use in clinical applications. Despite their capabilities, LLMs in the medical domain are prone to generating hallucinations (not fully reliable responses). Hallucinations in LLMs... | Xu J; Lu L; Peng X; Pang J; Ding J; Yang L; Song H; Li K; Sun X; Zhang S | 10 | |||
38875696 | Triage Performance Across Large Language Models, ChatGPT, and Untrained Doctors in Emergency Medicine: Comparative Study. | 2,024 | Journal of medical Internet research | BACKGROUND: Large language models (LLMs) have demonstrated impressive performances in various medical domains, prompting an exploration of their potential utility within the high-demand setting of emergency department (ED) triage. This study evaluated the triage proficiency of different LLMs and ChatGPT, an LLM-based c... | Masanneck L; Schmidt L; Seifert A; Kolsche T; Huntemann N; Jansen R; Mehsin M; Bernhard M; Meuth SG; Bohm L; Pawlitzki M | 10 | |||
37665620 | Artificial Intelligence in Medical Education: Comparative Analysis of ChatGPT, Bing, and Medical Students in Germany. | 2,023 | JMIR medical education | BACKGROUND: Large language models (LLMs) have demonstrated significant potential in diverse domains, including medicine. Nonetheless, there is a scarcity of studies examining their performance in medical examinations, especially those conducted in languages other than English, and in direct comparison with medical stud... | Roos J; Kasapovic A; Jansen T; Kaczmarczyk R | 21 | |||
40229614 | Evaluating the Efficacy of Large Language Models in Generating Medical Documentation: A Comparative Study of ChatGPT-4, ChatGPT-4o, and Claude. | 2,025 | Aesthetic plastic surgery | BACKGROUND: Large language models (LLMs) have demonstrated transformative potential in health care. They can enhance clinical and academic medicine by facilitating accurate diagnoses, interpreting laboratory results, and automating documentation processes. This study evaluates the efficacy of LLMs in generating surgica... | Lim B; Seth I; Maxwell M; Cuomo R; Ross RJ; Rozen WM | 10 | |||
40305085 | Accuracy of Large Language Models When Answering Clinical Research Questions: Systematic Review and Network Meta-Analysis. | 2,025 | Journal of medical Internet research | BACKGROUND: Large language models (LLMs) have flourished and gradually become an important research and application direction in the medical field. However, due to the high degree of specialization, complexity, and specificity of medicine, which results in extremely high accuracy requirements, controversy remains about... | Wang L; Li J; Zhuang B; Huang S; Fang M; Wang C; Li W; Zhang M; Gong S | 10 | |||
38343631 | Almanac - Retrieval-Augmented Language Models for Clinical Medicine. | 2,024 | NEJM AI | BACKGROUND: Large language models (LLMs) have recently shown impressive zero-shot capabilities, whereby they can use auxiliary data, without the availability of task-specific training examples, to complete a variety of natural language tasks, such as summarization, dialogue generation, and question answering. However, ... | Zakka C; Shad R; Chaurasia A; Dalal AR; Kim JL; Moor M; Fong R; Phillips C; Alexander K; Ashley E; Boyd J; Boyd K; Hirsch K; Langlotz C; Lee R; Melia J; Nelson J; Sallam K; Tullis S; Vogelsong MA; Cunningham JP; Hiesinger W | 10 | |||
40289855 | Evaluation of Six Large Language Models for Clinical Decision Support: Application in Transfusion Decision-making for RhD Blood-type Patients. | 2,025 | Annals of laboratory medicine | BACKGROUND: Large language models (LLMs) have the potential for clinical decision support; however, their use in specific tasks, such as determining the RhD blood type for transfusion, remains underexplored. Therefore, we evaluated the accuracy of six LLMs in addressing RhD blood type-related issues in Korean healthcar... | Lee JK; Choi S; Park S; Hwang SH; Cho D | 10 | |||
40217905 | Thyro-GenAI: A Chatbot Using Retrieval-Augmented Generative Models for Personalized Thyroid Disease Management. | 2,025 | Journal of clinical medicine | Background: Large language models (LLMs) have the potential to enhance information processing and clinical reasoning in the healthcare industry but are hindered by inaccuracies and hallucinations. The retrieval-augmented generation (RAG) technique may address these problems by integrating external knowledge sources. Me... | Shin M; Song J; Kim MG; Yu HW; Choe EK; Chai YJ | 10 | |||
40295957 | Utilizing Large language models to select literature for meta-analysis shows workload reduction while maintaining a similar recall level as manual curation. | 2,025 | BMC medical research methodology | BACKGROUND: Large language models (LLMs) like ChatGPT showed great potential in aiding medical research. A heavy workload in filtering records is needed during the research process of evidence-based medicine, especially meta-analysis. However, few studies tried to use LLMs to help screen records in meta-analysis. OBJEC... | Cai X; Geng Y; Du Y; Westerman B; Wang D; Ma C; Vallejo JJG | 10 | |||
40072530 | [Integration of large language models into the clinic : Revolution in analysing and processing patient data to increase efficiency and quality in radiology]. | 2,025 | Radiologie (Heidelberg, Germany) | BACKGROUND: Large Language Models (LLMs) like ChatGPT, Llama and Claude are transforming healthcare by interpreting complex text, extracting information, and providing guideline-based support. Radiology, with its high patient volume and digital workflows, is a ideal field for LLM integration. OBJECTIVE: Assessment of t... | Arnold P; Henkel M; Bamberg F; Kotter E | 10 | |||
40055694 | A systematic review of large language model (LLM) evaluations in clinical medicine. | 2,025 | BMC medical informatics and decision making | BACKGROUND: Large Language Models (LLMs), advanced AI tools based on transformer architectures, demonstrate significant potential in clinical medicine by enhancing decision support, diagnostics, and medical education. However, their integration into clinical workflows requires rigorous evaluation to ensure reliability,... | Shool S; Adimi S; Saboori Amleshi R; Bitaraf E; Golpira R; Tara M | 10 | |||
39591396 | Evaluation of a Large Language Model on the American Academy of Pediatrics' PREP Emergency Medicine Question Bank. | 2,024 | Pediatric emergency care | BACKGROUND: Large language models (LLMs), including ChatGPT (Chat Generative Pretrained Transformer), a popular, publicly available LLM, represent an important innovation in the application of artificial intelligence. These systems generate relevant content by identifying patterns in large text datasets based on user i... | Ramgopal S; Varma S; Gorski JK; Kester KM; Shieh A; Suresh S | 21 | |||
38051578 | ChatGPT Versus Consultants: Blinded Evaluation on Answering Otorhinolaryngology Case-Based Questions. | 2,023 | JMIR medical education | BACKGROUND: Large language models (LLMs), such as ChatGPT (Open AI), are increasingly used in medicine and supplement standard search engines as information sources. This leads to more "consultations" of LLMs about personal medical symptoms. OBJECTIVE: This study aims to evaluate ChatGPT's performance in answering clin... | Buhr CR; Smith H; Huppertz T; Bahr-Hamm K; Matthias C; Blaikie A; Kelsey T; Kuhn S; Eckrich J | 0-1 | |||
39019566 | Development and evaluation of a large language model of ophthalmology in Chinese. | 2,024 | The British journal of ophthalmology | BACKGROUND: Large language models (LLMs), such as ChatGPT, have considerable implications for various medical applications. However, ChatGPT's training primarily draws from English-centric internet data and is not tailored explicitly to the medical domain. Thus, an ophthalmic LLM in Chinese is clinically essential for ... | Zheng C; Ye H; Guo J; Yang J; Fei P; Yuan Y; Huang D; Huang Y; Peng J; Xie X; Xie M; Zhao P; Chen L; Zhang M | 21 | |||
37083633 | Trialling a Large Language Model (ChatGPT) in General Practice With the Applied Knowledge Test: Observational Study Demonstrating Opportunities and Limitations in Primary Care. | 2,023 | JMIR medical education | BACKGROUND: Large language models exhibiting human-level performance in specialized tasks are emerging; examples include Generative Pretrained Transformer 3.5, which underlies the processing of ChatGPT. Rigorous trials are required to understand the capabilities of emerging technology, so that innovation can be directe... | Thirunavukarasu AJ; Hassan R; Mahmood S; Sanghera R; Barzangi K; El Mukashfi M; Shah S | 21 | |||
37337531 | Evaluating the limits of AI in medical specialisation: ChatGPT's performance on the UK Neurology Specialty Certificate Examination. | 2,023 | BMJ neurology open | BACKGROUND: Large language models such as ChatGPT have demonstrated potential as innovative tools for medical education and practice, with studies showing their ability to perform at or near the passing threshold in general medical examinations and standardised admission tests. However, no studies have assessed their p... | Giannos P | 21 | |||
38261378 | Assessing ChatGPT's Mastery of Bloom's Taxonomy Using Psychosomatic Medicine Exam Questions: Mixed-Methods Study. | 2,024 | Journal of medical Internet research | BACKGROUND: Large language models such as GPT-4 (Generative Pre-trained Transformer 4) are being increasingly used in medicine and medical education. However, these models are prone to "hallucinations" (ie, outputs that seem convincing while being factually incorrect). It is currently unknown how these errors by large ... | Herrmann-Werner A; Festl-Wietek T; Holderried F; Herschbach L; Griewatz J; Masters K; Zipfel S; Mahling M | 21 | |||
40053752 | Detecting Artificial Intelligence-Generated Versus Human-Written Medical Student Essays: Semirandomized Controlled Study. | 2,025 | JMIR medical education | BACKGROUND: Large language models, exemplified by ChatGPT, have reached a level of sophistication that makes distinguishing between human- and artificial intelligence (AI)-generated texts increasingly challenging. This has raised concerns in academia, particularly in medicine, where the accuracy and authenticity of wri... | Doru B; Maier C; Busse JS; Lucke T; Schonhoff J; Enax-Krumova E; Hessler S; Berger M; Tokic M | 10 | |||
37099373 | Performance of ChatGPT on UK Standardized Admission Tests: Insights From the BMAT, TMUA, LNAT, and TSA Examinations. | 2,023 | JMIR medical education | BACKGROUND: Large language models, such as ChatGPT by OpenAI, have demonstrated potential in various applications, including medical education. Previous studies have assessed ChatGPT's performance in university or professional settings. However, the model's potential in the context of standardized admission tests remai... | Giannos P; Delardas O | 21 | |||
38153785 | Differentiating ChatGPT-Generated and Human-Written Medical Texts: Quantitative Study. | 2,023 | JMIR medical education | BACKGROUND: Large language models, such as ChatGPT, are capable of generating grammatically perfect and human-like text content, and a large number of ChatGPT-generated texts have appeared on the internet. However, medical texts, such as clinical notes and diagnoses, require rigorous validation, and erroneous medical c... | Liao W; Liu Z; Dai H; Xu S; Wu Z; Zhang Y; Huang X; Zhu D; Cai H; Li Q; Liu T; Li X | 10 | |||
39322838 | The Potential of Chat-Based Artificial Intelligence Models in Differentiating Between Keloid and Hypertrophic Scars: A Pilot Study. | 2,024 | Aesthetic plastic surgery | BACKGROUND: Lasting scars such as keloids and hypertrophic scars adversely affect a patient's quality of life. However, these scars are frequently underdiagnosed because of the complexity of the current diagnostic criteria and classification systems. This study aimed to explore the application of Large Language Models ... | Shiraishi M; Miyamoto S; Takeishi H; Kurita D; Furuse K; Ohba J; Moriwaki Y; Fujisawa K; Okazaki M | 0-1 | |||
39307579 | ChatGPT vs. sleep disorder specialist responses to common sleep queries: Ratings by experts and laypeople. | 2,024 | Sleep health | BACKGROUND: Many individuals use the Internet, including generative artificial intelligence like ChatGPT, for sleep-related information before consulting medical professionals. This study compared responses from sleep disorder specialists and ChatGPT to common sleep queries, with experts and laypersons evaluating the r... | Kim J; Lee SY; Kim JH; Shin DH; Oh EH; Kim JA; Cho JW | 0-1 | |||
38602313 | Importance of Patient History in Artificial Intelligence-Assisted Medical Diagnosis: Comparison Study. | 2,024 | JMIR medical education | BACKGROUND: Medical history contributes approximately 80% to a diagnosis, although physical examinations and laboratory investigations increase a physician's confidence in the medical diagnosis. The concept of artificial intelligence (AI) was first proposed more than 70 years ago. Recently, its role in various fields o... | Fukuzawa F; Yanagita Y; Yokokawa D; Uchida S; Yamashita S; Li Y; Shikino K; Tsukamoto T; Noda K; Uehara T; Ikusaka M | 10 | |||
38526538 | Performance of ChatGPT on the India Undergraduate Community Medicine Examination: Cross-Sectional Study. | 2,024 | JMIR formative research | BACKGROUND: Medical students may increasingly use large language models (LLMs) in their learning. ChatGPT is an LLM at the forefront of this new development in medical education with the capacity to respond to multidisciplinary questions. OBJECTIVE: The aim of this study was to evaluate the ability of ChatGPT 3.5 to co... | Gandhi AP; Joesph FK; Rajagopal V; Aparnavi P; Katkuri S; Dayama S; Satapathy P; Khatib MN; Gaidhane S; Zahiruddin QS; Behera A | 21 | |||
39712564 | Comparative evaluation of artificial intelligence systems' accuracy in providing medical drug dosages: A methodological study. | 2,024 | World journal of methodology | BACKGROUND: Medication errors, especially in dosage calculation, pose risks in healthcare. Artificial intelligence (AI) systems like ChatGPT and Google Bard may help reduce errors, but their accuracy in providing medication information remains to be evaluated. AIM: To evaluate the accuracy of AI systems (ChatGPT 3.5, C... | Ramasubramanian S; Balaji S; Kannan T; Jeyaraman N; Sharma S; Migliorini F; Balasubramaniam S; Jeyaraman M | 10 | |||
39257533 | Unlocking the potential of advanced large language models in medication review and reconciliation: A proof-of-concept investigation. | 2,024 | Exploratory research in clinical and social pharmacy | BACKGROUND: Medication review and reconciliation is essential for optimizing drug therapy and minimizing medication errors. Large language models (LLMs) have been recently shown to possess a lot of potential applications in healthcare field due to their abilities of deductive, abductive, and logical reasoning. The pres... | Sridharan K; Sivaramakrishnan G | 10 | |||
38287940 | Evaluating machine learning-enabled and multimodal data-driven exercise prescriptions for mental health: a randomized controlled trial protocol. | 2,024 | Frontiers in psychiatry | BACKGROUND: Mental illnesses represent a significant global health challenge, affecting millions with far-reaching social and economic impacts. Traditional exercise prescriptions for mental health often adopt a one-size-fits-all approach, which overlooks individual variations in mental and physical health. Recent advan... | Tan M; Xiao Y; Jing F; Xie Y; Lu S; Xiang M; Ren H | 0-1 | |||
37629452 | Comparing Meta-Analyses with ChatGPT in the Evaluation of the Effectiveness and Tolerance of Systemic Therapies in Moderate-to-Severe Plaque Psoriasis. | 2,023 | Journal of clinical medicine | BACKGROUND: Meta-analyses (MAs) and network meta-analyses (NMAs) are high-quality studies for assessing drug efficacy, but they are time-consuming and may be affected by biases. The capacity of artificial intelligence to aggregate huge amounts of information is emerging as particularly interesting for processing the vo... | Lam Hoai XL; Simonart T | 0-1 | |||
39184635 | The Role of Artificial Intelligence in the Primary Prevention of Common Musculoskeletal Diseases. | 2,024 | Cureus | BACKGROUND: Musculoskeletal disorders (MSDs) are a leading cause of disability worldwide, with a growing burden across all demographics. With advancements in technology, conversational artificial intelligence (AI) platforms such as ChatGPT (OpenAI, San Francisco, CA) have become instrumental in disseminating health inf... | Yilmaz Muluk S; Olcucu N | 32 | |||
36909565 | Assessing the Accuracy and Reliability of AI-Generated Medical Responses: An Evaluation of the Chat-GPT Model. | 2,023 | Research square | BACKGROUND: Natural language processing models such as ChatGPT can generate text-based content and are poised to become a major information source in medicine and beyond. The accuracy and completeness of ChatGPT for medical queries is not known. METHODS: Thirty-three physicians across 17 specialties generated 284 medic... | Johnson D; Goodman R; Patrinely J; Stone C; Zimmerman E; Donald R; Chang S; Berkowitz S; Finn A; Jahangir E; Scoville E; Reese T; Friedman D; Bastarache J; van der Heijden Y; Wright J; Carter N; Alexander M; Choe J; Chastain C; Zic J; Horst S; Turker I; Agarwal R; Osmundson E; Idrees K; Kieman C; Padmanabhan C; Bailey ... | 0-1 | |||
39156049 | Evaluating cognitive performance: Traditional methods vs. ChatGPT. | 2,024 | Digital health | BACKGROUND: NLP models like ChatGPT promise to revolutionize text-based content delivery, particularly in medicine. Yet, doubts remain about ChatGPT's ability to reliably support evaluations of cognitive performance, warranting further investigation into its accuracy and comprehensiveness in this area. METHOD: A cohort... | Fei X; Tang Y; Zhang J; Zhou Z; Yamamoto I; Zhang Y | 0-1 | |||
39305476 | Current application of ChatGPT in undergraduate nuclear medicine education: Taking Chongqing Medical University as an example. | 2,025 | Medical teacher | BACKGROUND: Nuclear Medicine(NM), as an inherently interdisciplinary field, integrates diverse scientific principles and advanced imaging techniques. The advent of ChatGPT, a large language model, opens new avenues for medical educational innovation. With its advanced natural language processing abilities and complex a... | Deng A; Chen W; Dai J; Jiang L; Chen Y; Chen Y; Jiang J; Rao M | 0-1 | |||
40139476 | Can a Large Language Model Interpret Data in the Electronic Health Record to Infer Minimum Clinically Important Difference Achievement of Knee Osteoarthritis Outcome Score-Joint Replacement Score Following Total Knee Arthroplasty? | 2,025 | The Journal of arthroplasty | BACKGROUND: Obtaining total knee arthroplasty patient-reported outcomes for quality assessment is costly and difficult. We asked whether a large language model (LLM) could interpret electronic health record notes to differentiate patients attaining a 1-year minimum clinically important difference (MCID) for the Knee Os... | Zalikha AK; Hong TS; Small EA; Constant M; Harris AHS; Giori NJ | 32 | |||
39635018 | Application of ChatGPT-4 to oculomics: a cost-effective osteoporosis risk assessment to enhance management as a proof-of-principles model in 3PM. | 2,024 | The EPMA journal | BACKGROUND: Oculomics is an emerging medical field that focuses on the study of the eye to detect and understand systemic diseases. ChatGPT-4 is a highly advanced AI model with multimodal capabilities, allowing it to process text and statistical data. Osteoporosis is a chronic condition presenting asymptomatically but ... | Choi JY; Han E; Yoo TK | 0-1 | |||
38976865 | ChatGPT With GPT-4 Outperforms Emergency Department Physicians in Diagnostic Accuracy: Retrospective Analysis. | 2,024 | Journal of medical Internet research | BACKGROUND: OpenAI's ChatGPT is a pioneering artificial intelligence (AI) in the field of natural language processing, and it holds significant potential in medicine for providing treatment advice. Additionally, recent studies have demonstrated promising results using ChatGPT for emergency medicine triage. However, its... | Hoppe JM; Auer MK; Struven A; Massberg S; Stremmel C | 10 | |||
39064053 | Assessing the Accuracy of Artificial Intelligence Models in Scoliosis Classification and Suggested Therapeutic Approaches. | 2,024 | Journal of clinical medicine | Background: Open-source artificial intelligence models (OSAIMs) are increasingly being applied in various fields, including IT and medicine, offering promising solutions for diagnostic and therapeutic interventions. In response to the growing interest in AI for clinical diagnostics, we evaluated several OSAIMs-such as ... | Fabijan A; Zawadzka-Fabijan A; Fabijan R; Zakrzewski K; Nowoslawska E; Polis B | 0-1 | |||
37987870 | "ChatGPT, Can You Help Me Save My Child's Life?" - Diagnostic Accuracy and Supportive Capabilities to Lay Rescuers by ChatGPT in Prehospital Basic Life Support and Paediatric Advanced Life Support Cases - An In-silico Analysis. | 2,023 | Journal of medical systems | BACKGROUND: Paediatric emergencies are challenging for healthcare workers, first aiders, and parents waiting for emergency medical services to arrive. With the expected rise of virtual assistants, people will likely seek help from such digital AI tools, especially in regions lacking emergency medical services. Large La... | Bushuven S; Bentele M; Bentele S; Gerber B; Bansbach J; Ganter J; Trifunovic-Koenig M; Ranisch R | 10 | |||
39445873 | Comparing Provider and ChatGPT Responses to Breast Reconstruction Patient Questions in the Electronic Health Record. | 2,024 | Annals of plastic surgery | BACKGROUND: Patient-directed Electronic Health Record (EHR) messaging is used as an adjunct to enhance patient-physician interactions but further burdens the physician. There is a need for clear electronic patient communication in all aspects of medicine, including plastic surgery. We can potentially utilize innovative... | Soroudi D; Gozali A; Knox JA; Parmeshwar N; Sadjadi R; Wilson JC; Lee SA; Piper ML | 32 | |||
39896176 | Exploring potential drug-drug interactions in discharge prescriptions: ChatGPT's effectiveness in assessing those interactions. | 2,025 | Exploratory research in clinical and social pharmacy | BACKGROUND: Potential drug-drug interactions (pDDIs) pose substantial risks in clinical practice, leading to increased morbidity, mortality, and healthcare costs. Tools like Micromedex drug-drug interaction checker are commonly used to screen for pDDIs, yet emerging AI models, such as ChatGPT, offer the potential for s... | Thapa RB; Karki S; Shrestha S | 10 | |||
39864953 | Classifying Unstructured Text in Electronic Health Records for Mental Health Prediction Models: Large Language Model Evaluation Study. | 2,025 | JMIR medical informatics | BACKGROUND: Prediction models have demonstrated a range of applications across medicine, including using electronic health record (EHR) data to identify hospital readmission and mortality risk. Large language models (LLMs) can transform unstructured EHR text into structured features, which can then be integrated into s... | Cardamone NC; Olfson M; Schmutte T; Ungar L; Liu T; Cullen SW; Williams NJ; Marcus SC | 10 | |||
38470459 | Capability of GPT-4V(ision) in the Japanese National Medical Licensing Examination: Evaluation Study. | 2,024 | JMIR medical education | BACKGROUND: Previous research applying large language models (LLMs) to medicine was focused on text-based information. Recently, multimodal variants of LLMs acquired the capability of recognizing images. OBJECTIVE: We aim to evaluate the image recognition capability of generative pretrained transformer (GPT)-4V, a rece... | Nakao T; Miki S; Nakamura Y; Kikuchi T; Nomura Y; Hanaoka S; Yoshikawa T; Abe O | 21 | |||
40164490 | Evaluating ChatGPT for converting clinic letters into patient-friendly language. | 2,025 | BJGP open | BACKGROUND: Previous research has shown that communication with patients in language they understand leads to greater comprehension of treatment and diagnoses but can be time consuming for clinicians. AIM: Here we sought to investigate the utility of ChatGPT to translate clinic letters into language patients understood... | Cork S; Hopcroft K | 10 | |||
39255030 | Prompt Engineering Paradigms for Medical Applications: Scoping Review. | 2,024 | Journal of medical Internet research | BACKGROUND: Prompt engineering, focusing on crafting effective prompts to large language models (LLMs), has garnered attention for its capabilities at harnessing the potential of LLMs. This is even more crucial in the medical domain due to its specialized terminology and language technicity. Clinical natural language p... | Zaghir J; Naguib M; Bjelogrlic M; Neveol A; Tannier X; Lovis C | 10 | |||
38239905 | ChatGPT is not ready yet for use in providing mental health assessment and interventions. | 2,023 | Frontiers in psychiatry | BACKGROUND: Psychiatry is a specialized field of medicine that focuses on the diagnosis, treatment, and prevention of mental health disorders. With advancements in technology and the rise of artificial intelligence (AI), there has been a growing interest in exploring the potential of AI language models systems, such as... | Dergaa I; Fekih-Romdhane F; Hallit S; Loch AA; Glenn JM; Fessi MS; Ben Aissa M; Souissi N; Guelmami N; Swed S; El Omri A; Bragazzi NL; Ben Saad H | 0-1 | |||
37040823 | Using a Google Web Search Analysis to Assess the Utility of ChatGPT in Total Joint Arthroplasty. | 2,023 | The Journal of arthroplasty | BACKGROUND: Rapid technological advancements have laid the foundations for the use of artificial intelligence in medicine. The promise of machine learning (ML) lies in its potential ability to improve treatment decision making, predict adverse outcomes, and streamline the management of perioperative healthcare. In an i... | Dubin JA; Bains SS; Chen Z; Hameed D; Nace J; Mont MA; Delanois RE | 32 | |||
39230947 | Evaluating the Capabilities of Generative AI Tools in Understanding Medical Papers: Qualitative Study. | 2,024 | JMIR medical informatics | BACKGROUND: Reading medical papers is a challenging and time-consuming task for doctors, especially when the papers are long and complex. A tool that can help doctors efficiently process and understand medical papers is needed. OBJECTIVE: This study aims to critically assess and compare the comprehension capabilities o... | Akyon SH; Akyon FC; Camyar AS; Hizli F; Sari T; Hizli S | 10 | |||
38148925 | The ability of artificial intelligence tools to formulate orthopaedic clinical decisions in comparison to human clinicians: An analysis of ChatGPT 3.5, ChatGPT 4, and Bard. | 2,024 | Journal of orthopaedics | BACKGROUND: Recent advancements in artificial intelligence (AI) have sparked interest in its integration into clinical medicine and education. This study evaluates the performance of three AI tools compared to human clinicians in addressing complex orthopaedic decisions in real-world clinical cases. QUESTIONS/PURPOSES:... | Agharia S; Szatkowski J; Fraval A; Stevens J; Zhou Y | 32 | |||
40209205 | Large Language Models in Biochemistry Education: Comparative Evaluation of Performance. | 2,025 | JMIR medical education | BACKGROUND: Recent advancements in artificial intelligence (AI), particularly in large language models (LLMs), have started a new era of innovation across various fields, with medicine at the forefront of this technological revolution. Many studies indicated that at the current level of development, LLMs can pass diffe... | Bolgova O; Shypilova I; Mavrych V | 21 | |||
40001164 | Quality assurance and validity of AI-generated single best answer questions. | 2,025 | BMC medical education | BACKGROUND: Recent advancements in generative artificial intelligence (AI) have opened new avenues in educational methodologies, particularly in medical education. This study seeks to assess whether generative AI might be useful in addressing the depletion of assessment question banks, a challenge intensified during th... | Ahmed A; Kerr E; O'Malley A | 21 | |||
39730155 | ChatGPT (GPT-4) versus doctors on complex cases of the Swedish family medicine specialist examination: an observational comparative study. | 2,024 | BMJ open | BACKGROUND: Recent breakthroughs in artificial intelligence research include the development of generative pretrained transformers (GPT). ChatGPT has been shown to perform well when answering several sets of medical multiple-choice questions. However, it has not been tested for writing free-text assessments of complex ... | Arvidsson R; Gunnarsson R; Entezarjou A; Sundemo D; Wikberg C | 21 | |||
39504445 | ChatGPT-4 Omni Performance in USMLE Disciplines and Clinical Skills: Comparative Analysis. | 2,024 | JMIR medical education | BACKGROUND: Recent studies, including those by the National Board of Medical Examiners, have highlighted the remarkable capabilities of recent large language models (LLMs) such as ChatGPT in passing the United States Medical Licensing Examination (USMLE). However, there is a gap in detailed analysis of LLM performance ... | Bicknell BT; Butler D; Whalen S; Ricks J; Dixon CJ; Clark AB; Spaedy O; Skelton A; Edupuganti N; Dzubinski L; Tate H; Dyess G; Lindeman B; Lehmann LS | 21 | |||
39496149 | Accuracy of Prospective Assessments of 4 Large Language Model Chatbot Responses to Patient Questions About Emergency Care: Experimental Comparative Study. | 2,024 | Journal of medical Internet research | BACKGROUND: Recent surveys indicate that 48% of consumers actively use generative artificial intelligence (AI) for health-related inquiries. Despite widespread adoption and the potential to improve health care access, scant research examines the performance of AI chatbot responses regarding emergency care advice. OBJEC... | Yau JY; Saadat S; Hsu E; Murphy LS; Roh JS; Suchard J; Tapia A; Wiechmann W; Langdorf MI | 43 | |||
39382347 | Registered Nurses' Attitudes Towards ChatGPT and Self-Directed Learning: A Cross-Sectional Study. | 2,024 | Journal of advanced nursing | BACKGROUND: Self-directed, lifelong learning is essential for nurses' competence in complex healthcare environments, which are characterised by rapid advancements in medicine and technology and nursing shortages. Previous studies have demonstrated that ChatGPT technology fosters self-directed learning by motivating use... | Chang LC; Wang YN; Lin HL; Liao LL | 10 | |||
40229613 | Man Versus Machine: A Comparative Study of Human and ChatGPT-Generated Abstracts in Plastic Surgery Research. | 2,025 | Aesthetic plastic surgery | BACKGROUND: Since its 2022 release, ChatGPT has gained recognition for its potential to expedite time-consuming writing tasks like scientific writing. Well-written scientific abstracts are essential for clear and efficient communication of research findings. This study aims to explore ChatGPT-4's capability to produce ... | Pressman SM; Garcia JP; Borna S; Gomez-Cabello CA; Haider SA; Haider CR; Forte AJ | 10 |
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