%0 Journal Article
        
%@ 2369-3762
%I JMIR Publications
%V 10
%N 
%P e63129
%T Performance of ChatGPT-4o on the Japanese Medical Licensing Examination: Evalution of Accuracy in Text-Only and Image-Based Questions
%A Miyazaki,Yuki
%A Hata,Masahiro
%A Omori,Hisaki
%A Hirashima,Atsuya
%A Nakagawa,Yuta
%A Eto,Mitsuhiro
%A Takahashi,Shun
%A Ikeda,Manabu
%K medical education
%K artificial intelligence
%K clinical decision-making
%K GPT-4o
%K medical licensing examination
%K Japan
%K images
%K accuracy
%K AI technology
%K application
%K decision-making
%K image-based
%K reliability
%K ChatGPT
%D 2024

%7 24.12.2024
%9 
%J JMIR Med Educ
%G English
                
%X This study evaluated the performance of ChatGPT with GPT-4 Omni (GPT-4o) on the 118th Japanese Medical Licensing Examination. The study focused on both text-only and image-based questions. The model demonstrated a high level of accuracy overall, with no significant difference in performance between text-only and image-based questions. Common errors included clinical judgment mistakes and prioritization issues, underscoring the need for further improvement in the integration of artificial intelligence into medical education and practice.
%R 10.2196/63129
%U https://mededu.jmir.org/2024/1/e63129
%U https://doi.org/10.2196/63129

%0 Journal Article
        
%@ 2369-3762
%I JMIR Publications
%V 10
%N 
%P e51435
%T ChatGPT May Improve Access to Language-Concordant Care for Patients With Non–English Language Preferences
%A Dzuali,Fiatsogbe
%A Seiger,Kira
%A Novoa,Roberto
%A Aleshin,Maria
%A Teng,Joyce
%A Lester,Jenna
%A Daneshjou,Roxana
%K ChatGPT
%K artificial intelligence
%K language
%K translation
%K health care disparity
%K natural language model
%K survey
%K patient education
%K preference
%K human language
%K language-concordant care
%D 2024

%7 10.12.2024
%9 
%J JMIR Med Educ
%G English
                
%X This study evaluated the accuracy of ChatGPT in translating English patient education materials into Spanish, Mandarin, and Russian. While ChatGPT shows promise for translating Spanish and Russian medical information, Mandarin translations require further refinement, highlighting the need for careful review of AI-generated translations before clinical use.
%R 10.2196/51435
%U https://mededu.jmir.org/2024/1/e51435
%U https://doi.org/10.2196/51435

%0 Journal Article
        
%@ 2369-3762
%I 
%V 10
%N 
%P e53193
%T The Utility of Wearable Cameras in Developing Examination Questions and Answers on Physical Examinations: Preliminary Study
%A Fukui,Sho
%A Shimizu,Taro
%A Nishizaki,Yuji
%A Shikino,Kiyoshi
%A Yamamoto,Yu
%A Kobayashi,Hiroyuki
%A Tokuda,Yasuharu
%K medical education
%K medical technology
%K wearable device
%K wearable camera
%K medical examination
%K exam
%K examination
%K exams
%K examinations
%K physical
%K resident physicians
%K wearable
%K wearables
%K camera
%K cameras
%K video
%K videos
%K innovation
%K innovations
%K innovative
%K recording
%K recordings
%K survey
%K surveys
%D 2024

%7 19.7.2024
%9 
%J JMIR Med Educ
%G English
                
%X To assess the utility of wearable cameras in medical examinations, we created a physician-view video-based examination question and explanation, and the survey results indicated that these cameras can enhance the evaluation and educational capabilities of medical examinations.
%R 10.2196/53193
%U https://mededu.jmir.org/2024/1/e53193
%U https://doi.org/10.2196/53193

%0 Journal Article
        
%@ 2369-3762
%I 
%V 10
%N 
%P e54283
%T The Performance of ChatGPT-4V in Interpreting Images and Tables in the Japanese Medical Licensing Exam
%A Takagi,Soshi
%A Koda,Masahide
%A Watari,Takashi
%K ChatGPT
%K medical licensing examination
%K generative artificial intelligence
%K medical education
%K large language model
%K images
%K tables
%K artificial intelligence
%K AI
%K Japanese
%K reliability
%K medical application
%K medical applications
%K diagnostic
%K diagnostics
%K online data
%K web-based data
%D 2024

%7 23.5.2024
%9 
%J JMIR Med Educ
%G English
                
%X 
%R 10.2196/54283
%U https://mededu.jmir.org/2024/1/e54283
%U https://doi.org/10.2196/54283

%0 Journal Article
        
%@ 2369-3762
%I 
%V 10
%N 
%P e56568
%T Collaborative Development of an Electronic Portfolio to Support the Assessment and Development of Medical Undergraduates
%A dos Santos,Luiz Ricardo Albano
%A de Oliveira,Alan Maicon
%A dos Santos,Luana Michelly Aparecida Costa
%A Aguilar,Guilherme José
%A Costa,Wilbert Dener Lemos
%A Donato,Dantony de Castro Barros
%A Bollela,Valdes Roberto
%K e-portfolio
%K education
%K health education
%K learning
%K medical students
%K medical school curriculum
%K medical education
%K student support
%K software
%D 2024

%7 4.4.2024
%9 
%J JMIR Med Educ
%G English
                
%X This study outlines the development of an electronic portfolio (e-portfolio) designed to capture and record the overall academic performance of medical undergraduate students throughout their educational journey. Additionally, it facilitates the capture of narratives on lived experiences and sharing of reflections, fostering collaboration between students and their mentors.
%R 10.2196/56568
%U https://mededu.jmir.org/2024/1/e56568
%U https://doi.org/10.2196/56568

%0 Journal Article
        
%@ 2369-3762
%I JMIR Publications
%V 10
%N 
%P e52155
%T Using AI Text-to-Image Generation to Create Novel Illustrations for Medical Education: Current Limitations as Illustrated by Hypothyroidism and Horner Syndrome
%A Kumar,Ajay
%A Burr,Pierce
%A Young,Tim Michael
%+ Queen Square Institute of Neurology, University College London, Number 7 Queen Square, London, WC1N 3BG, United Kingdom, 44 2031082781, t.young@ucl.ac.uk
%K artificial intelligence
%K AI
%K medical illustration
%K medical images
%K medical education
%K image
%K images
%K illustration
%K illustrations
%K photo
%K photos
%K photographs
%K face
%K facial
%K paralysis
%K photograph
%K photography
%K Horner's syndrome
%K Horner syndrome
%K Bernard syndrome
%K Bernard's syndrome
%K miosis
%K oculosympathetic
%K ptosis
%K ophthalmoplegia
%K nervous system
%K autonomic
%K eye
%K eyes
%K pupil
%K pupils
%K neurologic
%K neurological
%D 2024

%7 22.2.2024
%9 Research Letter
%J JMIR Med Educ
%G English
                
%X Our research letter investigates the potential, as well as the current limitations, of widely available text-to-image tools in generating images for medical education. We focused on illustrations of important physical signs in the face (for which confidentiality issues in conventional patient photograph use may be a particular concern) that medics should know about, and we used facial images of hypothyroidism and Horner syndrome as examples.
%M 38386400
%R 10.2196/52155
%U https://mededu.jmir.org/2024/1/e52155
%U https://doi.org/10.2196/52155
%U http://www.ncbi.nlm.nih.gov/pubmed/38386400

%0 Journal Article
        
%@ 2369-3762
%I JMIR Publications
%V 9
%N 
%P e48780
%T Anki Tagger: A Generative AI Tool for Aligning Third-Party Resources to Preclinical Curriculum
%A Pendergrast,Tricia
%A Chalmers,Zachary
%+ Northwestern University Feinberg School of Medicine, 303 E Chicago Ave, Morton 1-670, Chicago, IL, 60611, United States, 1 3125038194, zachary.chalmers@northwestern.edu
%K ChatGPT
%K undergraduate medical education
%K large language models
%K Anki
%K flashcards
%K artificial intelligence
%K AI
%D 2023

%7 20.9.2023
%9 Research Letter
%J JMIR Med Educ
%G English
                
%X Using large language models, we developed a method to efficiently query existing flashcard libraries and select those most relevant to an individual's medical school curricula.
%M 37728965
%R 10.2196/48780
%U https://mededu.jmir.org/2023/1/e48780
%U https://doi.org/10.2196/48780
%U http://www.ncbi.nlm.nih.gov/pubmed/37728965