Journal of Frontiers of Computer Science and Technology ›› 2022, Vol. 16 ›› Issue (10): 2219-2233.DOI: 10.3778/j.issn.1673-9418.2112118

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Research and Application Progress of Chinese Medical Knowledge Graph

FAN Yuanyuan, LI Zhongmin+()   

  1. College of Life Science, Central South University, Changsha 410013, China
  • Received:2021-12-29 Revised:2022-05-13 Online:2022-10-01 Published:2022-10-14
  • About author:FAN Yuanyuan, born in 1997, M.S. candidate. Her research interests include organization of information and knowledge graph.
    LI Zhongmin, born in 1971, Ph.D., associate professor, M.S. supervisor. Her research interests include medical informatics and medical information organization.
  • Supported by:
    Fundamental Research Funds for the Central Universities of Central South University(2021zzts0558);Postgraduate Scientific Research Innovation Project of Hunan Province(CX20210122)


范媛媛, 李忠民+()   

  1. 中南大学 生命科学学院,长沙 410013
  • 通讯作者: + E-mail:
  • 作者简介:范媛媛(1997—),女,河南孟州人,硕士研究生,主要研究方向为信息组织、知识图谱。
  • 基金资助:


Knowledge graph is a large-scale semantic network that gives machine background knowledge. Using knowledge graph to organize heterogeneous medical information can effectively improve the utilization value of massive medical resources and promote the development of medical intelligence. This paper describes the research, construction and application status of knowledge graph in medical field from three dimensions: the key technology of knowledge graph, the construction of medical knowledge graph and the application of medical knowledge graph, and explores the topics worthy of research in the future. Firstly, the development of knowledge representation, knowledge extraction, knowledge fusion and knowledge inference are systematically summarized, their latest progress is discussed, and the technical difficulties in the construction of Chinese medical knowledge graph are analyzed. Secondly, the existing research on Chinese medical knowledge graph is illustrated from three perspectives of medical ontology, general practice knowledge graph and single disease medical knowledge graph. The research characteristics of Chinese medical knowledge graph are also analyzed. Finally, the application of medical know-ledge graph in semantic search, decision support and intelligent question answering are analyzed, and the new app-lication scenarios are discussed. In view of the challenges faced by Chinese medical knowledge graph, such as low standardization of terminology, lack of annotated corpus, insufficient technical research and limitations of applica-tion scenarios, the future research directions of Chinese medical knowledge graph are prospected.

Key words: medical knowledge graph, knowledge representation, knowledge extraction, decision support, intelli-gent question answering



关键词: 医学知识图谱, 知识表示, 知识抽取, 决策支持, 智能问答

CLC Number: