Medical Knowledge Graph: Data Sources, Construction, Reasoning, and Applications
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 en...
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| Published in | Big Data Mining and Analytics Vol. 6; no. 2; pp. 201 - 217 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Beijing
Tsinghua University Press
01.06.2023
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| Subjects | |
| Online Access | Get full text |
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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. |
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| AbstractList | 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. |
| Author | Duan, Junwen Pan, Yi Li, Min Wu, Xuehong |
| Author_xml | – sequence: 1 givenname: Xuehong surname: Wu fullname: Wu, Xuehong organization: School of Computer Science and Engineering, Central South University,Changsha,China,410083 – sequence: 2 givenname: Junwen surname: Duan fullname: Duan, Junwen organization: School of Computer Science and Engineering, Central South University,Changsha,China,410083 – sequence: 3 givenname: Yi surname: Pan fullname: Pan, Yi organization: Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences,Faculty of Computer Science and Control Engineering,Shenzhen,China,518000 – sequence: 4 givenname: Min surname: Li fullname: Li, Min organization: School of Computer Science and Engineering, Central South University,Changsha,China,410083 |
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| Title | Medical Knowledge Graph: Data Sources, Construction, Reasoning, and Applications |
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