PDF下载

[1]李春晓芮欣凯.基于大语言模型及电子病历的临床医学NLP系统构建：以患者饮酒信息分析为例[J].中国卫生质量管理,2025,32(12):18-22.[doi:10.13912/j.cnki.chqm.2025.32.12.04]
　LI Chunxiao,RUI Xinkai.Construction of a Clinical Medicine NLP System Based on Large Language Models and Electronic Medical Records: a Case Study of Patient Alcohol Consumption Information Analysis[J].Chinese Health Quality Management,2025,32(12):18-22.[doi:10.13912/j.cnki.chqm.2025.32.12.04]

点击复制

基于大语言模型及电子病历的临床医学NLP系统构建：以患者饮酒信息分析为例

《中国卫生质量管理》[ISSN:1006-7515/CN:CN 61-1283/R] 卷: 32 期数: 2025年12期页码: 18-22 栏目: 特别关注出版日期: 2025-12-15

Title:: Construction of a Clinical Medicine NLP System Based on Large Language Models and Electronic Medical Records: a Case Study of Patient Alcohol Consumption Information Analysis

作者:: 李春晓芮欣凯; 上海交通大学医学院附属瑞金医院

Author(s):: LI Chunxiao; RUI Xinkai; Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine

关键词:: 大语言模型; 自然语言处理; 特征选择; 电子病历

Keywords:: Large Language Model; Natural Language Processing; Feature Selection; Electronic Medical Record

分类号:: R197.323

DOI:: 10.13912/j.cnki.chqm.2025.32.12.04

文献标志码:: B

摘要:: 以患者饮酒信息分析为切入点，使用多种算法及机器学习模型，构建了一种结合分类规则与大语言模型的临床医学自然语言处理系统。该系统可以识别电子病历中的患者饮酒信息，并对整份病历所包含的饮酒状态进行标记。与已有自然语言处理系统相比，该系统更贴合中文病历语言特点，并在细粒度饮酒状态识别上表现突出，为电子病历文本的智能化分析提供了参考路径。

Abstract:: This study takes the analysis of patient alcohol consumption information as the entry point, employing multiple algorithms and machine learning models to construct a clinical medicine natural language processing system that integrates classification rules with large language models. This system is capable of identifying patient alcohol consumption information within electronic medical records and labeling the alcohol consumption status encompassed in the entire medical record. Compared with existing natural language processing systems, this research is more aligned with the linguistic characteristics of Chinese medical records and demonstrates outstanding performance in fine-grained alcohol consumption status recognition, providing a reference pathway for the intelligent analysis of Chinese electronic medical records texts.

参考文献/References:

［1］刘丹红,罗小楠,徐勇勇.电子病历及其应用概述［J］.中国卫生质量管理,2010,17(4):2-5,1.［2］BAGNARDI V, ROTA M, BOTTERI E, et al. Light alcohol drinking and cancer：a meta-analysis［J］. Ann Oncol, 2013, 24(2):301-308.［3］ARONSON AR, LANG FM. An overview of MetaMap: historical perspective and recent advances［J］.J Am Med Inform Assoc, 2010, 17(3):229-236.［4］LINDBERG DAB, HUMPHREYS BL, MCCRAY AT. The united medical language system［J］.Method Inform Med, 1993, 32(4):281-291.［5］JAIN NL, KNIRSCH CA, FRIEDMAN C, et al. Identification of suspected tuberculosis patients based on natural language processing of chest radiograph reports.［J］.Proc Amia Annu Fall Symp, 1996(1):542-546.［6］HUA X, STENNER SP, SOU D, et al. MedEx： a medication information extraction system for clinical narratives［J］. J Am Med Inform Assoc, 2010, 17(1):19-24.［7］NADKARNI P, CHEN R, BRANDT C, et al.UMLS concept indexing for production databases: a feasibility study［J］. J Am Med Inform Assoc, 2001, 8(1):512.［8］娄苗苗,张浩,刘丹红.医疗质量测量指标基础数据的标准化方法［J］.中国卫生质量管理,2013,20(2):53-56.［9］舒婷,赵韡,刘海一.2020年我国医院电子病历系统应用水平分析［J］.中国卫生质量管理,2022,29(1):8-10,20.［10］盛文佳,金可可,费宏玮,等.基于临床路径的电子病历改进思路［J］.中国卫生质量管理,2011,18(5):18-20.［11］孟晓阳.电子病历互操作性的实现技术［J］.中国卫生质量管理,2010,17(4):19-21.［12］OGREN P,SAVOVA GK,CHUTE CG.Constructing evaluation corpora for automated clinical named entity recognition［C］. In 6th International Conference on Language Resources & Evaluation.DBLP, 2010.［13］张华平,商建云.NLPIR-Parser:大数据语义智能分析平台［J］.语料库语言学,2019,6(1):87-104.［14］JOACHIMS T.Text categorization with support vector machines: learning with many relevant features［C］. In 10th European Conference on Machine Learning, 1998:137-142.［15］要芳.基于本体的电子病历知识库研究［D］.西安:西安电子科技大学,2009.［16］CHAPMAN WW, BRIDEWELL W, HANBURY P, et al. A simple algorithm for identifying negated findings and diseases in discharge summaries［J］.J Biomed Inform, 2001, 34(5):301-310.［17］吉旭瑞,魏德健,张俊忠,等.中文电子病历信息提取方法研究综述［J］.计算机工程与科学,2024,46(2):325-337.［18］HALL M, FRANK E, HOLMES G, et al. The WEKA data mining software：an update［J］.ACM SIGKDD Explor Newsl, 2008, 11(1):10-18.［19］YANG Y. An evaluation of statistical approaches to text categorization［J］.Proc Amia Annu Fall Symp, 1999, 1(1-2):358-362.

相似文献/References:

[1]吴丹麦张晓丽侯旭敏.基于大语言模型的智慧医院热点主题演变研究[J].中国卫生质量管理,2025,32(02):1.[doi:10.13912/j.cnki.chqm.2025.32.2.01]
　WU Danmai,ZHANG Xiaoli,HOU Xumin.Research on the Evolution of Hot Topics in Smart Hospitals Based on Large Language Model[J].Chinese Health Quality Management,2025,32(12):1.[doi:10.13912/j.cnki.chqm.2025.32.2.01]
[2]武思齐庞潇李丹妮郭薇刘济远黄艳.人工智能在口腔互联网医院健康管理中的应用研究[J].中国卫生质量管理,2025,32(12):8.[doi:10.13912/j.cnki.chqm.2025.32.12.02]
　WU Siqi,PANG Xiao,LI Danni.Research on the Application of Artificial Intelligence in Health Management of Oral Internet Hospitals[J].Chinese Health Quality Management,2025,32(12):8.[doi:10.13912/j.cnki.chqm.2025.32.12.02]
[3]丁勇蔡秀军庞晓燕朱慧兰赵钫婷.大语言模型驱动的医疗服务数字化转型：“邵医通”智能语音客服的构建逻辑与实践启示[J].中国卫生质量管理,2026,33(1):55.[doi:10.13912/j.cnki.chqm.2026.33.1.12]
　DING Yong,CAI Xiujun,PANG Xiaoyan.Digital Transformation of Healthcare Services Driven by Large Language Models: the Construction Logic and Practical Implications of the "ShaoYiTong" Intelligent Voice Customer Service[J].Chinese Health Quality Management,2026,33(12):55.[doi:10.13912/j.cnki.chqm.2026.33.1.12]
[4]李大玮陈委娜单晓丽刘鹏焦淑贤.献血咨询服务系统的设计与应用[J].中国卫生质量管理,2026,33(3):67.[doi:10.13912/j.cnki.chqm.2026.33.3.15]
　LI Dawei,CHEN Weina,SHAN Xiaoli.Research on the Design and Application of Blood Donation Consultation Service System[J].Chinese Health Quality Management,2026,33(12):67.[doi:10.13912/j.cnki.chqm.2026.33.3.15]
[5]鞠鑫徐爱彬张正欣张哲来.大语言模型技术在医疗卫生行业数据分类分级中的应用与效果分析[J].中国卫生质量管理,2026,33(5):23.[doi:10.13912/j.cnki.chqm.2026.33.5.05]
　JU Xin,XU Aibin,ZHANG Zhengxin.Analysis of the Application and Effects of LLM Technology in Data Classification and Grading within the Healthcare Industry[J].Chinese Health Quality Management,2026,33(12):23.[doi:10.13912/j.cnki.chqm.2026.33.5.05]

更新日期/Last Update: 2025-12-15