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电子病历命名实体识别和实体关系抽取研究综述

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摘要 

电子病历(Electronic medical records,EMR)产生于临床治疗过程,其中命名实体和实体关系反映了患者健康状况,包含了大量与患者健康状况密切相关的医疗知识,因而对它们的识别和抽取是信息抽取研究在医疗领域的重要扩展. 本文首先讨论了电子病历文本的语言特点和结构特点,然后在梳理了命名实体识别和实体关系抽取研究一般思路的基础上,分析了电子病历命名实体识别、实体修饰识别和实体关系抽取研究的具体任务和对应任务的主要研究方法. 本文还介绍了相关的共享评测任务和标注语料库以及医疗领域几个重要的词典和知识库等资源. 最后对这一研究领域仍需解决的问题和未来的发展方向作了展望.

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收稿日期: 2013-08-30     

基金资助:

国家自然科学基金(60975077)资助

通讯作者: 关毅 哈尔滨工业大学教授. 主要研究方向为智能信息检索,网络挖掘,自然语言处理,,认知语言学.E-mail:guanyi@hit.edu.cn     E-mail: guanyi@hit.edu.cn

作者简介: 杨锦锋 哈尔滨工业大学博士研究生.主要研究方向为自然语言处理,电子病历信息抽取.E-mail:yangjinfeng2010@gmail.com

引用本文:   

杨锦锋, 于秋滨, 关毅, 蒋志鹏. 电子病历命名实体识别和实体关系抽取研究综述. 自动化学报, 2014, 40(8): 1537-1562.
Yang Jin-Feng, YU Qiu-Bin, GUAN Yi, JIANG Zhi-Peng. An Overview of Research on Electronic Medical Record Oriented Named Entity Recognition and Entity Relation Extraction. Acta Automatica Sinica, 2014, 40(8): 1537-1562.

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