The large amount of medical information carried in the electronic medical record can help doctors better understand the situation of patients and assist doctors in clinical diagnosis.As the two core tasks of Chinese electronic medical record(EMR)information extraction,named entity recognition and entity relationship extraction have become the main research directions.Its main goal is to identify the medical entities in the EMR text and extract the medical relationships between the entities.This pa-per systematically expounds the research status of Chinese electronic medical record,points out the im-portant role of named entity recognition and entity relationship extraction in Chinese electronic medical record information extraction,then introduces the latest research results of named entity recognition and relationship extraction algorithm for Chinese electronic medical record information extraction,and ana-lyzes the advantages and disadvantages of each model in each stage.In addition,the current problems of Chinese EMR are discussed,and the future research trend is prospected.
关键词
中文电子病历/命名实体识别/实体关系抽取/自然语言处理/深度学习
Key words
Chinese electronic medical record/named entity identification/entity relationship extrac-tion/natural language processing/deep learning
维普
万方数据