Shaw Kody, Henning Marcus A, Webster Craig S
Centre for Medical and Health Sciences Education, School of Medicine, University of Auckland, Auckland, New Zealand.
Med Sci Educ. 2025 Apr 2;35(3):1803-1816. doi: 10.1007/s40670-025-02373-0. eCollection 2025 Jun.
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.
人工智能（AI）已展现出临床潜力，但其对医学教育的影响仍然有限。本综述探讨了人工智能在医学教育中的应用，评估了现有证据，并思考了未来的应用。我们进行了一项范围综述（通过PubMed、MEDLINE、SCOPUS、谷歌学术搜索；2010 - 2022年），共识别出42篇相关的同行评议文章。出现了四个关键主题：外科技能评估、放射学培训、交互式学习和文本解读。当前的应用增强了手术模拟并促进了交互式学习。这些工具可能会朝着全面且个性化的教育辅助工具发展。尽管早期应用前景广阔，但关于教育和临床结果的证据仍然有限。未来的研究应优先在更大规模的试验中验证结果，以确认其可推广性并解决人工智能的局限性。
