摘要
目的:探讨人工智能在中医药领域的研究热点及前沿方向,为今后的研究提供参考及借鉴。方法:以中国知网(CNKI)和Web of Science(WoS)中人工智能在中医药学领域相关文献为数据来源,结合人工梳理及信息整合的方法,运用CiteSpace软件对文献分布、作者、机构、关键词、共被引文献进行统计分析。结果:共纳入中文文献691篇,英文文献168篇,2018—2019年中英文文献数量大幅度增加;作者以近年来新兴团队为主,机构合作模式单一,高被引论文较少;研究方法主要是数据挖掘、机器学习、深度学习、神经网络及遗传算法,应用领域主要是中医智能诊断及预测各类疾病进程、中药智能识别分类、中医健康养生,研究成果主要是中医养生保健的智能化设备、中医人工智能系统、中医知识库、中医药学语言系统等。结论:人工智能在中医药领域的研究热点集中于中医智能方法、智能诊断及智能预测,热点更趋向于智能方法研究,各研究团队及研究机构应当加强各研究领域专家合作,实现多学科融合发展。
Objective: To discusses the research focus and forward direction of artificial intelligence in the field of traditional Chinese medicine, and to provide reference for the later research. Methods: Based on the literature of artificial intelligence in the field of traditional Chinese medicine in CNKI and Web of Science as the data source, combined with the method of artificial combing and information integration, a statistical analysis of literature distribution, authors, institutions and keywords was carried out by using CiteSpace software. Results:A total of 691 Chinese literatures and 168 English literatures were included, and the number of Chinese and English literatures increased significantly from 2018 to 2019. The authors were mainly emerging teams in recent years, the cooperation mode of institutions was single, and highly cited papers were less. The main research methods are data mining, machine learning, deep learning, neural network and genetic algorithm. The main application fields are intelligent diagnosis and prediction of various diseases, intelligent recognition and classification of traditional Chinese medicine, and health preservation of traditional Chinese medicine. The research results are mainly intelligent equipment of TCM health care, TCM artificial intelligence system, TCM knowledge base, TCM language system, etc. Conclusion: The research focuses on intelligent methods of TCM, intelligent diagnosis and intelligent prediction, and the research focuses on intelligent methods. Research teams and research institutions should break down the research barriers and strengthen the cooperation among experts in various research fields,to realize the development of multi-disciplinary integration.
作者
张君冬
杨硕
ZHANG Jun-dong;YANG Shuo(Institute of Information on Traditional Chinese Medicine,China Academy of Chinese Medical Sciences,Beijing 100700,China)
出处
《中医药导报》
2021年第1期151-155,162,共6页
Guiding Journal of Traditional Chinese Medicine and Pharmacy
基金
中国中医科学院自主选题项目(ZZ11-054,ZZ140315)。
关键词
中医药
人工智能
CiteSpace软件
可视化分析
研究热点
traditional Chinese medicine
artificial intelligence
CiteSpace software
visual analysis
research hotspot
