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

被引:47
|
作者
Wu, Xuehong [1 ,2 ]
Duan, Junwen [1 ]
Pan, Yi [3 ]
Li, Min [1 ]
机构
[1] Cent South Univ, Sch Comp Sci & Engn, Changsha 410083, Peoples R China
[2] Hunan First Normal Univ, Sch Comp Sci, Changsha 410006, Peoples R China
[3] Chinese Acad Sci, Shenzhen Inst Adv Technol, Fac Comp Sci & Control Engn, Shenzhen 518000, Peoples R China
基金
中国国家自然科学基金;
关键词
Biomedical equipment; Soft sensors; Biological system modeling; Medical services; Big Data; Cognition; Data mining; medical knowledge graph; knowledge graph construction; knowledge reasoning; intelligent medical applications; intelligent healthcare; FRAMEWORK; SYSTEM; EXTRACTION;
D O I
10.26599/BDMA.2022.9020021
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:201 / 217
页数:17
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