Research and Application Progress of Chinese Medical Knowledge Graph

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 de...

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Main Author: FAN Yuanyuan, LI Zhongmin
Format: Article
Language:zho
Published: Journal of Computer Engineering and Applications Beijing Co., Ltd., Science Press 2022-10-01
Series:Jisuanji kexue yu tansuo
Subjects:
Online Access:http://fcst.ceaj.org/fileup/1673-9418/PDF/1673-9418-16-10-2219.pdf
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author FAN Yuanyuan, LI Zhongmin
author_facet FAN Yuanyuan, LI Zhongmin
author_sort FAN Yuanyuan, LI Zhongmin
collection DOAJ
description 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.
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spelling doaj.art-c876573a3f564ee79ab7cd028a20f8a82022-12-22T03:39:33ZzhoJournal of Computer Engineering and Applications Beijing Co., Ltd., Science PressJisuanji kexue yu tansuo1673-94182022-10-0116102219223310.3778/j.issn.1673-9418.2112118Research and Application Progress of Chinese Medical Knowledge GraphFAN Yuanyuan, LI Zhongmin0College of Life Science, Central South University, Changsha 410013, ChinaKnowledge 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.http://fcst.ceaj.org/fileup/1673-9418/PDF/1673-9418-16-10-2219.pdf|medical knowledge graph|knowledge representation|knowledge extraction|decision support|intelli-gent question answering
spellingShingle FAN Yuanyuan, LI Zhongmin
Research and Application Progress of Chinese Medical Knowledge Graph
Jisuanji kexue yu tansuo
|medical knowledge graph|knowledge representation|knowledge extraction|decision support|intelli-gent question answering
title Research and Application Progress of Chinese Medical Knowledge Graph
title_full Research and Application Progress of Chinese Medical Knowledge Graph
title_fullStr Research and Application Progress of Chinese Medical Knowledge Graph
title_full_unstemmed Research and Application Progress of Chinese Medical Knowledge Graph
title_short Research and Application Progress of Chinese Medical Knowledge Graph
title_sort research and application progress of chinese medical knowledge graph
topic |medical knowledge graph|knowledge representation|knowledge extraction|decision support|intelli-gent question answering
url http://fcst.ceaj.org/fileup/1673-9418/PDF/1673-9418-16-10-2219.pdf
work_keys_str_mv AT fanyuanyuanlizhongmin researchandapplicationprogressofchinesemedicalknowledgegraph