中华医学教育杂志

中华医学教育杂志 >

2025 , Vol. 45 >Issue 3: 187 - 193

DOI: https://doi.org/10.3760/cma.j.cn115259-20240715-00736

人工智能在医学教育中的应用

人工智能在毕业后医学教育中的应用与挑战

  • 谢文加 ,
  • 王筝扬
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  • 1浙江大学医学院附属邵逸夫医院眼科,杭州 310016;
    2浙江大学医学院附属邵逸夫医院教育办公室,杭州 310016

收稿日期: 2024-07-15

  网络出版日期: 2025-03-04

基金资助

国家重点研发计划(2023YFE0204200);浙江大学AI For Education系列实证教学研究项目(重点项目序号3);浙江大学AI For Education系列实证教学研究项目(一般项目序号5)

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Applications and challenges of artificial intelligence in postgraduate medical education

  • Xie Wenjia ,
  • Wang Zhengyang
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  • 1Department of Ophthalmology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310016, China;
    2Department of Education Administration, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310016, China

Received date: 2024-07-15

  Online published: 2025-03-04

Supported by

National Key R & D Program of China (2023YFE0204200); “AI for Education”Teaching Research Project of Zhejiang University (Key Project No. 3); “AI for Education”Teaching Research Project of Zhejiang University (General Project No. 5)

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摘要

人工智能(artificial intelligence, AI)技术的引入正在逐步重塑医学教育的面貌。近年来,以辅助诊断AI和生成式AI为代表,AI技术在毕业后医学教育中得到了日益广泛且深入的应用。本文介绍了AI在毕业后医学教育中辅助教学实施、辅助自主学习和辅助评估与反馈的应用进展,展示其提升教学效率与质量,促进临床能力的精准培训与个性化培养,推动医师从传统学习向人机协同新模式过渡的能力和潜力。本文还对AI技术带来的伦理问题、数据安全、教育公平性、技术接受度和“医学+AI”交叉人才培养等一系列挑战进行了探讨。

关键词： 人工智能; 生成式AI; 毕业后医学教育; 住院医师规范化培训; 应用; 挑战

本文引用格式

谢文加 , 王筝扬 . 人工智能在毕业后医学教育中的应用与挑战[J]. 中华医学教育杂志, 2025 , 45(3) : 187 -193 . DOI: 10.3760/cma.j.cn115259-20240715-00736

Abstract

The integration of Artificial Intelligence (AI) technology is progressively reshaping the medical education. In recent years, represented by diagnostic assistance AI and generative AI, AI technology has been increasingly and extensively applied in various aspects of postgraduate medical education. This review introduces the progress of AI applications in postgraduate medical education, including assistance in teaching implementation, self-directed learning, and assessment and feedback. The review demonstrates the ability and potential of AI to enhance teaching efficiency and quality, promote precise and personalized clinical competence development, and facilitate the transition of physicians from traditional learning to a new model of human-computer collaboration. The review also discusses the challenges generated by AI technology, such as ethical issues, data security, educational equity, technology acceptance, and the cultivation of “medicine + AI” interdisciplinary professionals.

Key words： Artificial intelligence; Generative AI; Postgraduate medical education; Residency training; Application; Challenge

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