摘要
大语言模型、多模态模型和智能体技术的发展，使生成式人工智能从单纯的知识问答工具逐步拓展至病例生成、临床推理辅助、技能训练、个性化反馈和教学评价等医学实践教育环节。这一应用不仅能够提高医学实践教育的效率和个性化程度，也对患者安全、医学伦理、职业责任、科学精神和医患沟通提出了新的要求。本文梳理生成式人工智能在医学实践教育中的主要应用场景及其潜在价值，并以放射科住院医师规范化培训为例，重点分析其在影像病例讨论、报告书写训练、循证决策学习、形成性评价和医学人文教育中的实践路径。在此基础上，提炼以患者为中心、坚持科学精神、强化责任意识、维护数据安全和促进医学创新等思政教育内涵，提出“课前准备—课堂实践—课后反思”的教学实施框架。同时，针对医学知识错误、数据隐私风险、技术过度依赖和责任边界不清等问题，提出相应的教学管理与安全控制建议，为生成式人工智能时代医学实践教育改革提供参考。
关键词： 生成式人工智能；医学实践教育；课程思政；放射科；住院医师规范化培训；医学人文；人工智能素养
Abstract
With the advancement of large language models, multimodal models and intelligent agents, generative artificial intelligence (AI) is expanding from a question-answering tool to multiple links of medical practice education, including case generation, clinical reasoning assistance, skill training, personalized feedback and teaching evaluation. The application of generative AI improves the efficiency and individualization of medical practice education, and at the same time raises new requirements for patient safety, medical ethics, professional responsibility, scientific spirit and doctor-patient communication. This article reviews the main application scenarios and potential values of generative AI in medical practice education. Taking radiology standardized residency training as an example, it analyzes the practical pathways of generative AI in imaging case discussion, radiology report writing training, evidence-based learning, formative assessment and medical humanities education. On this basis, the ideological and political education implications, including patient-centeredness, scientific spirit, responsibility awareness, data security and medical innovation, are extracted, and a teaching implementation framework of “pre-class preparation—in-class practice—post-class reflection” is proposed. Meanwhile, in response to problems such as medical knowledge hallucination, data privacy risks, over-reliance on technology and unclear responsibility boundaries, corresponding suggestions on teaching management and safety control are put forward, aiming to provide reference for the reform of medical practice education in the era of generative AI.
Key words： Generative artificial intelligence; Medical practice education; Curriculum ideological and political education; Radiology; Standardized residency training; Medical humanities; Artificial intelligence literacy
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