{"title":"chatgpt - 40在日本医疗执照考试中的表现:纯文本和基于图像问题的准确性评估。","authors":"Yuki Miyazaki, Masahiro Hata, Hisaki Omori, Atsuya Hirashima, Yuta Nakagawa, Mitsuhiro Eto, Shun Takahashi, Manabu Ikeda","doi":"10.2196/63129","DOIUrl":null,"url":null,"abstract":"<p><strong>Unlabelled: </strong>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.</p>","PeriodicalId":36236,"journal":{"name":"JMIR Medical Education","volume":"10 ","pages":"e63129"},"PeriodicalIF":3.2000,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11687171/pdf/","citationCount":"0","resultStr":"{\"title\":\"Performance of ChatGPT-4o on the Japanese Medical Licensing Examination: Evalution of Accuracy in Text-Only and Image-Based Questions.\",\"authors\":\"Yuki Miyazaki, Masahiro Hata, Hisaki Omori, Atsuya Hirashima, Yuta Nakagawa, Mitsuhiro Eto, Shun Takahashi, Manabu Ikeda\",\"doi\":\"10.2196/63129\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Unlabelled: </strong>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.</p>\",\"PeriodicalId\":36236,\"journal\":{\"name\":\"JMIR Medical Education\",\"volume\":\"10 \",\"pages\":\"e63129\"},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2024-12-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11687171/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"JMIR Medical Education\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2196/63129\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"EDUCATION, SCIENTIFIC DISCIPLINES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"JMIR Medical Education","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2196/63129","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"EDUCATION, SCIENTIFIC DISCIPLINES","Score":null,"Total":0}
引用次数: 0
摘要
未标记:本研究评估了ChatGPT与GPT-4 Omni (gpt - 40)在第118届日本医疗执照考试中的表现。这项研究主要集中在纯文本和基于图像的问题上。该模型总体上显示出很高的准确性,纯文本和基于图像的问题在性能上没有显著差异。常见的错误包括临床判断错误和优先顺序问题,强调需要进一步改进将人工智能融入医学教育和实践。
Performance of ChatGPT-4o on the Japanese Medical Licensing Examination: Evalution of Accuracy in Text-Only and Image-Based Questions.
Unlabelled: 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.