Computer Science ›› 2023, Vol. 50 ›› Issue (3): 83-93.doi: 10.11896/jsjkx.220700241

• Special Issue of Knowledge Engineering Enabled By Knowledge Graph: Theory, Technology and System • Previous Articles     Next Articles

Survey of Medical Knowledge Graph Research and Application

JIANG Chuanyu, HAN Xiangyu, YANG Wenrui, LYU Bohan, HUANG Xiaoou, XIE Xia, GU Yang   

  1. School of Computer Science and Technology,Hainan University,Haikou 570288,China
  • Received:2022-07-25 Revised:2022-12-19 Online:2023-03-15 Published:2023-03-15
  • About author:JIANG Chuanyu,born in 1999,postgraduate,is a member of China Computer Federation.His main research interest is knowledge graph.
    GU Yang,born in 1975,master.His main research interests include image recognition and data analysis.
  • Supported by:
    Hainan Province Science and Technology Special Fund(ZDKJ2021042).

Abstract: In the process of digitisation of medical data,choosing the right technology for efficient processing and accurate analysis of medical data is a common problem faced by the medical field today.The use of knowledge graph technology with the excellent association and reasoning capabilities to process and analyse medical data can better enable applications such as wise information technology of medicine and aided diagnoses.The complete process of constructing a medical knowledge graph includes know-ledge extraction,knowledge fusion and knowledge reasoning.Knowledge extraction can be subdivided into entity extraction,relationship extraction and attribute extraction,while knowledge fusion mainly includes entity alignment and entity disambiguation.Firstly,the constructiontechnologies and practical applications of medical knowledge graphs are summarised,and the development of the technologies is clarified for each specific construction process.On this basis,the relevant techniques are introduced,and their advantages and limitations are explained.Secondly,introducing several medical knowledge graphs that are being successfully applied.Finally,based on the current state of technology and applications of knowledge graphs in the medical field,future research directions for knowledge graphs in technology and applications are given.

Key words: Medicine, Big data, Knowledge graph, Data processing, Knowledge graph construction technology

CLC Number: 

  • TP181
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