eepSeek赋能医学教育：特点、影响与应对
目的/意义 目前，国产人工智能(AI)大语言模型(LLM)深度求索(DeepSeek)迅猛发展，已经影响通信、金融、医疗、汽车等多个领域。作为医学教育工作者，要敏锐地发现DeepSeek为医学教育带来的机遇与挑战。 方法/过程 本文聚焦DeepSeek的技术架构与开源策略、本土化优势和可视化推理三大特点，探讨DeepSeek相较以GPT为代表的LLMs如何通过对教学资源、教学体验、教学生态三方面的影响更好地赋能人才培养。 结果/结论 医学教育工作者应重新反思教育与学习的本质，确保DeepSeek真正高效地运用于医学教育。
Abstract: Purpose/Significance At present,the rapid development of domestic artificial intelligence (AI) large language model (LLM) DeepSeek has affected many fields such as communications,finance,medical treatment,and automobiles. As medical educators,we should be keenly aware of the opportunities and challenges that DeepSeek brings to medical education. Method/Process This paper focuses on the three characteristics of DeepSeek's:technical architecture,open source strategy,localization advantage,and visual reasoning,exploring how DeepSeek can better empower talent cultivation through the impact of teaching resources,teaching experience,and teaching ecology compared with LLMs represented by GPT. Result/Conclusion Medical educators should rethink the nature of education and learning to ensure that DeepSeek is truly and effectively applied to medical education.
武凡祺、许超
兰州大学第二医院;兰州大学第二临床医学院兰州大学第二临床医学院
医学现状、医学发展教育
人工智能大语言模型eepSeek医学教育教育教学
artificial intelligencelarge language modeleepSeekmedical educationeducation and teaching
武凡祺,许超.eepSeek赋能医学教育：特点、影响与应对[EB/OL].(2025-04-12)[2025-08-04].https://www.biomedrxiv.org.cn/article/doi/bmr.202504.00033.点此复制
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