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自由文本电子病历信息抽取综述
引用本文:崔博文,金涛,王建民.自由文本电子病历信息抽取综述[J].计算机应用,2021,41(4):1055-1063.
作者姓名:崔博文  金涛  王建民
作者单位:清华大学 软件学院, 北京 100084
基金项目:国家自然科学基金资助项目
摘    要:电子病历信息抽取技术能够从自由文本电子病历中获取到有用的关键信息,从而为医院的信息管理和后续的信息分析处理工作提供帮助。简要介绍了现阶段自由文本电子病历信息抽取的主要流程,分析了近十几年来关于自由文本电子病历中命名实体、实体修饰与实体间关系三类关键信息的单独抽取以及联合抽取方法的研究成果,对这些成果所采用的主要方法、使用的数据集、最终的实验效果等进行了对比总结。除此之外,还对最新的几种流行方法的特点以及优缺点进行了分析,对目前电子病历信息抽取领域常用数据集进行了总结,分析了目前国内相关领域的现状和发展趋势。

关 键 词:信息抽取  命名实体识别  实体修饰识别  实体关系抽取  电子病历  
收稿时间:2020-06-11
修稿时间:2020-10-13

Overview of information extraction of free-text electronic medical records
CUI Bowen,JIN Tao,WANG Jianmin.Overview of information extraction of free-text electronic medical records[J].journal of Computer Applications,2021,41(4):1055-1063.
Authors:CUI Bowen  JIN Tao  WANG Jianmin
Affiliation:School of Software, Tsinghua University, Beijing 100084, China
Abstract:Information extraction technology can extract the key information in free-text electronic medical records, helping the information management and subsequent information analysis of the hospital. Therefore, the main process of free-text electronic medical record information extraction was simply introduced, the research results of single extraction and joint extraction methods for three most important types of information:named entity, entity assertion and entity relation in the past few years were studied, and the methods, datasets, and final effects of these results were compared and summarized. In addition, an analysis of the features, advantages and disadvantages of several popular new methods, a summarization of commonly used datasets in the field of information extraction of free-text electronic medical records, and an analysis of the current status and research directions of related fields in China was carried out.
Keywords:information extraction  named entity recognition  entity assertion detection  entity relation extraction  electronic medical record  
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