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人工智能在临床推理教学新模式中的研究及展望
Research progress and prospects of artificial intelligence in new models of clinical reasoning education
- 中华医学教育探索杂志 2025年24卷第10期 页码：1372-1378
- 作者机构：
中国医学科学院/北京协和医学院/北京协和医院全科医学科（普通内科），北京 100730
- 作者简介：
焦洋，Email：peterpumch@163.com
- 基金信息：中央高水平医院临床科研专项(2022-PUMCH-A-017);北京协和医院教育创新与改革项目(CMB-JYCXGG04)
DOI：10.3760/cma.j.cn116021-20250310-02066
中图分类号： R-4收稿：2025-03-10，
纸质出版：2025-10-20
- 稿件说明：
移动端阅览
徐赫, 焦洋. 人工智能在临床推理教学新模式中的研究及展望[J]. 中华医学教育探索杂志, 2025, 24(10): 1372-1378.
Xu He, Jiao Yang. Research progress and prospects of artificial intelligence in new models of clinical reasoning education[J]. Chinese journal of medical education research, 2025, 24(10): 1372-1378.
徐赫, 焦洋. 人工智能在临床推理教学新模式中的研究及展望[J]. 中华医学教育探索杂志, 2025, 24(10): 1372-1378. DOI： 10.3760/cma.j.cn116021-20250310-02066.
Xu He, Jiao Yang. Research progress and prospects of artificial intelligence in new models of clinical reasoning education[J]. Chinese journal of medical education research, 2025, 24(10): 1372-1378. DOI： 10.3760/cma.j.cn116021-20250310-02066.
摘要
人工智能（artificial intelligence，AI）技术的发展正在驱动医学教育模式转型，其中临床推理（clinical reasoning）教学领域的变革尤为显著。传统临床推理教学模式依赖资深医师通过真实案例进行经验传授，而新技术的涌现使AI逐渐成为教学过程中的关键要素。本研究综述并分析近5年相关研究发现，AI技术通过4个核心要素构建临床推理教学新路径：基于AI的智能案例系统（用于材料准备）、虚拟病人教学系统（推理能力训练）、智能评分系统（实现能力评估），以及全程嵌入的AI决策支持系统。循证研究表明，AI在临床案例整合和真实情景模拟方面展现出优势，但其在提供临床推理信息的可靠性、时效性以及对学生临床推理能力长期影响方面仍需进一步验证。现阶段实践建议采用传统教学与新路径相结合的双轨制教学模式，在关键决策点保留人工审核环节，以有效控制AI可能带来的错误风险；在未来，具备临床推理能力的AI模型有望为医学教育提供更为可靠的支持。
Abstract
The advancement of artificial intelligence (AI) technology has initiated a paradigm shift in medical education
particularly transforming the field of clinical reasoning training. While traditional training models rely on experienced physicians imparting knowledge through real clinical cases
the new technological revolution empowers AI to play an increasingly significant role in educational processes. Through reviewing and analyzing research data from the past five years on AI-assisted clinical reasoning education
this paper reveals that AI technology establishes a novel clinical reasoning education pathway through four core modules: AI-based intelligent case system (material preparation)
virtual patient educational system (reasoning skill development)
intelligent scoring system (competency assessment)
and AI decision support system integrated throughout the process. Evidence-based research demonstrates the advantages of AI in clinical case integration and teaching based on realistic scenario simulation. However
the reliability and timeliness of AI-provided clinical reasoning information and its long-term impacts on students' clinical reasoning capabilities require further verification. Currently
a dual-track teaching model that integrates traditional and novel approaches is recommended
with human oversight maintained at critical decision points to effectively mitigate potential risks of decision errors posed by AI. In the future
AI models with clinical reasoning capabilities hold promise for providing more reliable support in medical education.
关键词
Keywords
references
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