Research progress on information extraction methods of Chinese electronic medical records

Abstract

Abstract: 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 paper systematically expounds the research status of Chinese electronic medical record, points out the important 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 analyzes 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.

Key words: Chinese electronic medical record, named entity identification, entity relationship extraction, natural language processing, deep learning

JI Xu-rui, WEI De-jian, ZHANG Jun-zhong, ZHANG Shuai, CAO Hui. Research progress on information extraction methods of Chinese electronic medical records[J]. Computer Engineering & Science, 2024, 46(02): 325-337.

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Research progress on information extraction methods of Chinese electronic medical records

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