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

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,并绘制相关科学知识图谱。结果共纳入文献428篇,最早关于中医辅助诊断研究的论文发表于1981年。近40年来,中医计算机辅助诊断研究有2个研究高峰时期,分别为1989-1992年和2001-2010年。主要合作团队有吕汉兴团队、李海鲲团队、杨学智团队和温川飙团队,形成以北京中医药大学、湖南中医药大学、南京中医药大学为核心的研究机构网络,研究机构之间合作较少。中医类研究机构占比44.40%,非医学类研究机构占比36.51%。研究内容集中在中医专家系统、中医电脑诊疗系统、中医辨证论治模型、中医诊断客观化、中医诊断智能化5个方面;前沿热点主要集中在中医药的知识发现、人工智能、机器学习、神经网络、知识图谱研究等方面。结论随着信息技术的进步和大数据、人工智能技术的广泛应用,中医计算机辅助诊断逐渐客观化、精确化、智能化,其研究深度和广度也不断拓展和延伸。

Knowledge Map Analysis on Research Hotspots and Trends in Computer-aided Diagnosis of TCM in China

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.