DeepSeek与医学大语言模型:技术创新与医疗服务模式重构  

DeepSeek and Medical Large Language Model:Technological Innovation and Reconstruction of Medical Service Mode

作　　者：闾海荣 江瑞[1] 张学工[1] 王存库 LYU Hairong;JIANG Rui;ZHANG Xuegong;WANG Cunku(Life Foundation Model Laboratory,Department of Automation,Tsinghua University,Beijing 100084,China)

机构地区：[1]清华大学自动化系生命基础模型实验室,北京100084

出　　处：《医学信息学杂志》2025年第2期1-7,13,共8页Journal of Medical Informatics

基　　金：国家重点研发计划(项目编号:2022YFF1202400)。

摘　　要：目的/意义从DeepSeek出发,探讨医学大语言模型的技术创新,以应对医学领域独有的技术难题和挑战。方法/过程重点分析医疗人工智能在多模态数据融合、医生思维方式适配以及医疗决策高风险性的技术要求等方面的突破路径,并展望未来医学大语言模型如何推动数智医院建设与医疗服务模式重构。结果/结论随着人工智能技术的不断发展,医学大语言模型将在未来医疗实践中发挥越来越重要的作用。通过多模态数据融合、因果推理的引入、模型可解释性的提升,大语言模型不仅能提升诊断效率和准确性,还将为数智医院的建设和医疗服务模式重构提供强有力的技术支持。Purpose/Significance Starting from DeepSeek,the paper explores the technological innovation and challenges of medical large language models,in order to address the unique technical difficulties and challenges in the medical field.Method/Process It focuses on analyzing the breakthrough path of medical artificial intelligence(AI)in multimodal data fusion,adaptation of doctors’thinking patterns,and technical requirements for high-risk medical decision-making,and looks forward the construction of the smart hospitals and the reconstruction of medical service modes using medical large language models in the future.Result/Conclusion With the continuous development of AI technology,medical large language models will play an important role in future medical practice.By integrating multimodal data,introducing causal reasoning,and improving model interpretability,large language models can not only enhance diagnostic efficiency and accuracy,but also provide strong technical support for the construction of digital and smart hospitals and the reconstruction of medical service modes.

关 键 词：大语言模型 医学服务模式 DeepSeek 

分 类 号：R-058[医药卫生]