DeepSeek在临床医学见习教学中的应用

中图分类号：G642.4 文献标志码：A 文章编号：2096-3181（2025）04-0564-07

Abstract： Clinical medical clerkship，a critical transitional phase for medical students entering clinical practice， faces challenges in traditional teaching modes such as limited case resources，uneven distribution of faculty， and delayed feedback. Large language models （LLMs）like DeepSeek demonstrate innovative potential by generating virtual cases，simulating dynamic disease progression，and enabling multimodal interactions， thereby overcoming temporal-spatial constraints and case variety limitations in conventional education. Its intellgent decision support system enhances clinical reasoning through evidence-based diagnostic and therapeutic pathway analysis，treatment plan comparisons，and doctor-patient communication simulations. However，AI applications encounter technical and ethical challenges including medical knowledge“halucinations”，privacy risks，and homogenization of clinical thinking.Toaddress these，a human-AI collaborative teaching mode needs to be established，clarifying the roleof AI in standardized training and the role of teachers in advanced cognitive development.Multi-tier medical knowledge verification mechanisms should be established，strengthening data security and ethical decision-making systems. In addition，“Questioning AI" training modules should be designed to cultivate critical thinking.Focusing on DeepSeek’s practical implementation in medical clerkship，it provides dual-dimensional insights into technological empowerment and educational ethics，so as to provide reference for constructing AI-driven medical education paradigms.

Keywords： LLMs; Clinical medical clerkship teaching; Virtual case simulation; Clinical decision support; Educational ethics

临床医学见习是医学生从理论学习向临床实践过渡的关键阶段，这一过程不仅需要学生掌握疾病诊疗的规范化流程，更要求其培养临床思维、医患沟通和应急决策等核心能力。（剩余12391字）