检验医学 ›› 2025, Vol. 40 ›› Issue (11): 1042-1046.DOI: 10.3969/j.issn.1673-8640.2025.11.002

• 专家论坛 • 上一篇    下一篇

大语言模型在检验医学中的应用和展望

杨大干   

  1. 浙江大学医学院附属第一医院检验科,浙江 杭州 310003
  • 收稿日期:2025-05-23 修回日期:2025-08-16 出版日期:2025-11-30 发布日期:2025-12-12
  • 作者简介:杨大干,男,1975年生,硕士,主任技师,主要从事临床实验室管理和数据科学研究。
  • 基金资助:
    国家重点研发计划项目(2022YFC3602302)

Application and prospect of large language models in laboratory medicine

YANG Dagan   

  1. Department of Clinical Laboratory,the First Affiliated Hospital,Zhejiang University School of Medicine,Hangzhou 310003,Zhejiang,China
  • Received:2025-05-23 Revised:2025-08-16 Online:2025-11-30 Published:2025-12-12

摘要:

DeepSeek、ChatGPT等大语言模型(LLM)为临床实验室信息生态圈提供了智能基座,助力实现智慧检验。目前,LLM尚存在缺乏应用场景实现方案、缺乏全生命周期管理、未针对检验医学领域进行微调等局限。文章介绍LLM在检验前、中、后阶段和实验室管理等应用场景的技术方案及其预期效果,构建LLM全生命周期的管理框架,通过提示词工程、检索增强生成、微调等技术实现LLM与检验医学的深度融合。同时,文章阐述了目前LLM的应用特点、面临的挑战,以及应对策略,为进一步推进智慧检验的发展提供参考。

关键词: 人工智能, 大语言模型, 检验医学, 报告解读, 检索增强生成

Abstract:

Large language models (LLM) such as DeepSeek and ChatGPT provide an intelligent foundation for laboratory information ecosystem,facilitating the realization of intelligent laboratory medicine. At present,LLM still have limitations,such as the lack of application scenario implementation solutions,the absence of full life cycle management and no fine-tuning for laboratory medicine. This review introduces the technical solutions and expected effects of LLM in application scenarios,such as pre-,intra- and post-laboratory determination and laboratory management,constructs a management framework for the full life cycle of LLM,and realizes the deep integration of LLM and laboratory medicine through technologies,such as prompt engineering,retrieval augmented generation and fine-tuning. This review expounds the current application characteristics,challenges and countermeasures of LLM as well,providing a reference for further promoting the development of intelligent laboratory medicine.

Key words: Artificial intelligence, Large language model, Laboratory medicine, Report interpretation, Retrieval augmented generation

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