{"title":"Artificial Intelligence in Medical Education: a Scoping Review of the Evidence for Efficacy and Future Directions.","authors":"Kody Shaw, Marcus A Henning, Craig S Webster","doi":"10.1007/s40670-025-02373-0","DOIUrl":null,"url":null,"abstract":"<p><p>Artificial intelligence (AI) has demonstrated clinical potential, yet its influence on medical education remains limited. This review explores AI applications in medical education, evaluates available evidence and considers future applications. We conducted a scoping review (PubMed, MEDLINE, SCOPUS, Google Scholar; 2010-2022) identifying 42 relevant peer-reviewed articles. Four key themes emerged: surgical skills assessment, radiology training, interactive learning, and text interpretation. Current applications enhance surgical simulation and facilitate interactive learning. These tools may evolve towards comprehensive and individualised educational aids. Despite promising early applications, evidence on educational and clinical outcomes remains limited. Future research should prioritise validated outcomes in larger trials to confirm generalisability and address AI limitations.</p>","PeriodicalId":37113,"journal":{"name":"Medical Science Educator","volume":"35 3","pages":"1803-1816"},"PeriodicalIF":1.9000,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12228863/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Medical Science Educator","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s40670-025-02373-0","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/6/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"EDUCATION, SCIENTIFIC DISCIPLINES","Score":null,"Total":0}
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Abstract
Artificial intelligence (AI) has demonstrated clinical potential, yet its influence on medical education remains limited. This review explores AI applications in medical education, evaluates available evidence and considers future applications. We conducted a scoping review (PubMed, MEDLINE, SCOPUS, Google Scholar; 2010-2022) identifying 42 relevant peer-reviewed articles. Four key themes emerged: surgical skills assessment, radiology training, interactive learning, and text interpretation. Current applications enhance surgical simulation and facilitate interactive learning. These tools may evolve towards comprehensive and individualised educational aids. Despite promising early applications, evidence on educational and clinical outcomes remains limited. Future research should prioritise validated outcomes in larger trials to confirm generalisability and address AI limitations.
期刊介绍：
Medical Science Educator is the successor of the journal JIAMSE. It is the peer-reviewed publication of the International Association of Medical Science Educators (IAMSE). The Journal offers all who teach in healthcare the most current information to succeed in their task by publishing scholarly activities, opinions, and resources in medical science education. Published articles focus on teaching the sciences fundamental to modern medicine and health, and include basic science education, clinical teaching, and the use of modern education technologies. The Journal provides the readership a better understanding of teaching and learning techniques in order to advance medical science education.
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