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Open Access

Medical Knowledge Graph: Data Sources, Construction, Reasoning, and Applications

Xuehong Wu1,2,†, Junwen Duan1,†, Yi Pan3, Min Li1( )
School of Computer Science and Engineering, Central South University, Changsha 410083, China
School of Computer Science, Hunan First Normal University, Changsha 410006, China
Faculty of Computer Science and Control Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518000, China

† Xuehong Wu and Junwen Duan contribute equally to this work.

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Abstract

Medical knowledge graphs (MKGs) are the basis for intelligent health care, and they have been in use in a variety of intelligent medical applications. Thus, understanding the research and application development of MKGs will be crucial for future relevant research in the biomedical field. To this end, we offer an in-depth review of MKG in this work. Our research begins with the examination of four types of medical information sources, knowledge graph creation methodologies, and six major themes for MKG development. Furthermore, three popular models of reasoning from the viewpoint of knowledge reasoning are discussed. A reasoning implementation path (RIP) is proposed as a means of expressing the reasoning procedures for MKG. In addition, we explore intelligent medical applications based on RIP and MKG and classify them into nine major types. Finally, we summarize the current state of MKG research based on more than 130 publications and future challenges and opportunities.

Keywords

medical knowledge graphknowledge graph constructionknowledge reasoningintelligent medical applicationsintelligent healthcare

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Big Data Mining and Analytics
Volume 6 Issue 2,
June 2023
Pages 201-217
DOI: 10.26599/BDMA.2022.9020021
Cite this article:
Wu X, Duan J, Pan Y, et al. Medical Knowledge Graph: Data Sources, Construction, Reasoning, and Applications. Big Data Mining and Analytics, 2023, 6(2): 201-217. https://doi.org/10.26599/BDMA.2022.9020021

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Received: 03 July 2022
Accepted: 13 July 2022
Published: 26 January 2023
© The author(s) 2023.

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