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我国中医计算机辅助诊断研究热点与趋势的知识图谱分析
引用本文:石英杰,李宗友,赵攀,杨硕,刘成源. 我国中医计算机辅助诊断研究热点与趋势的知识图谱分析[J]. 中国中医药图书情报杂志, 2021, 0(2): 11-18
作者姓名:石英杰  李宗友  赵攀  杨硕  刘成源
作者单位:中国中医科学院中医药信息研究所;中国中医科学院眼科医院;国家中医药管理局服务中心
基金项目:国家重点研发计划(2017YFB1002300)。
摘    要:
目的 分析我国近40年中医计算机辅助诊断研究的相关文献,探索该领域发展现状、研究热点及前沿动态,为后期研究提供参考和借鉴.方法 检索中国知识资源总库(CNKI)自建库至2020年10月31日发表的中医计算机辅助诊断研究相关文献,运用CiteSpace v.5.7.R2软件对发文量、作者、发文机构、关键词进行分析挖掘,并...

关 键 词:中医  辅助诊断  CiteSpace  科学知识图谱  热点  演变趋势

Knowledge Map Analysis on Research Hotspots and Trends in Computer-aided Diagnosis of TCM in China
SHI Ying-jie,LI Zong-you,ZHAO Pan,YANG Shuo,LIU Cheng-yuan. Knowledge Map Analysis on Research Hotspots and Trends in Computer-aided Diagnosis of TCM in China[J]. Chinese Journal of Library and Information Science for TraditionalChinese Medicine, 2021, 0(2): 11-18
Authors:SHI Ying-jie  LI Zong-you  ZHAO Pan  YANG Shuo  LIU Cheng-yuan
Affiliation:(Institute of Information on Traditional Chinese Medicine,China Academy of Chinese Medical Sciences,Beijing 100700,China;Eye Hospital,China Academy of Chinese Medical Sciences,Beijing 100040,China;Service Center of National Administration of Traditional Chinese Medicine,Beijing 100027,China)
Abstract:
Objective To analyze the relevant literature of research on computer-aided diagnosis of TCM in the past 40 years in China;To explore the development status, research hotspots and frontier trends of this field;To provide reference for further research. Methods Research related literature on computer-aided diagnosis of TCM published by CNKI from its establishment to October 31, 2020 was retrieved. CiteSpace v.5.7.R2 software was used to analyze and mine the amount of articles, authors, publication organizations, and keywords, and relevant scientific knowledge maps were drawn. Results Totally 428 articles were included, and the earliest article on the research of auxiliary diagnosis of TCM was published in 1981. In the past 40 years, there have been two research peak periods for computer-aided diagnosis of TCM, namely 1989–1992 and 2001–2010. The main cooperation teams included Lu Hanxing’s team, Li Haikun’s team, Yang Xuezhi’s team and Wen Chuanbiao’s team, forming a network of research institutions centered on Beijing University of Chinese Medicine, Hunan University of Chinese Medicine, and Nanjing University of Chinese Medicine. There was little cooperation between research institutions. TCM research institutions accounted for 44.40%, and non-medical research institutions accounted for 36.51%. The research contents focused on five aspects: TCM expert system, TCM computerized diagnosis and treatment system, TCM syndrome differentiation and treatment model, TCM diagnosis objectification, and TCM diagnosis intelligence;frontier hotspots mainly focused on knowledge discovery, AI, machine learning, neural networks, and knowledge map research on TCM. Conclusion computeraided diagnosis of TCM has gradually become objectified, precise and intelligent, and its research depth and breadth have also been continuously expanded and extended.
Keywords:TCM  aided diagnosis  CiteSpace  scientific knowledge map  hotspots  evolution trend
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