史纪元;田金徽;高亚;许建国;李峥;
SHI Jiyuan;TIAN Jinhui;GAO Ya;XU Jian'guo;LI Zheng;School of Nursing,Chinese Academy of Medical Sciences & Peking Union Medical College;Evidence-Based Medicine Center,Lanzhou University;Key Laboratory of Evidence-based Medicine and Knowledge Translation of Gansu Province,Lanzhou University;

• 1:中国医学科学院北京协和医学院护理学院
• 2:兰州大学循证医学中心
• 3:兰州大学甘肃省循证医学与临床转化重点实验室

摘要(Abstract)：

目的 探究人工智能(artificial intelligence, AI)在医学领域应用的随机对照试验(randomized controlled trial, RCT)研究现状，以期为我国学者开展AI研究提供思路。方法 检索PubMed数据库，获得AI相关RCT医学研究文献。基于Web of Science数据库获取文献发表时间、被引频次、作者及所在研究机构与国家等信息，并进行归纳总结；采用VOSviewer 1.6.17软件生成作者、研究机构、国家合作的网络图，并对关键词进行聚类分析；采用Cite Space 5.8.R3软件对文献被引情况和关键词进行突发性检测。结果 共获得医学领域内AI相关RCT文献1174篇，篇均被引频次为36.09,发表时间分布于1989至2021年，其中2007年后发文量显著增加。1174篇研究共涉及61个国家、1794个机构、7288位作者，其中发文量居前5位的国家依次为美国(37.22%,437篇)、意大利(10.90%,128篇)、韩国(8.86%,104篇)、德国(8.35%,98篇)、中国(7.84%,92篇),发文量居前5位的研究机构分别为美国哈佛大学(2.98%,35篇)、韩国延世大学(2.73%,32篇)、美国西北大学(2.21%,26篇)、美国麻省理工学院(2.13%,25篇)、美国斯坦福大学(1.96%,23篇),发文量居前5位的作者分别为Krebs(22篇，美国麻省理工学院)、Calabro(11篇，意大利IRCCS神经中心)、Picelli (11篇，意大利维罗纳大学)、Smania(11篇，意大利维罗纳大学)、Lin(10篇，中国台湾大学)。高产作者、研究机构、国家之间的合作不充分、不密切。高频关键词聚集为3类：机器人技术在疾病治疗中的应用、机器学习在疾病诊断与管理中的应用和AI在康复训练中的应用。突发性检测结果发现，机器人辅助和机器学习是目前该领域内的研究热点。结论 近年来AI相关RCT医学研究数量增加迅速，虽然发达国家在该领域的研究处于领先地位，但我国的研究者和研究机构亦表现出巨大潜力。目前开展AI相关RCT医学研究的作者、研究机构及国家之间的合作不密切，研究主题有待拓展。
Objective To explore the research status of randomized controlled trial(RCT) with theapplication of artificial intelligence(AI) in the medical field, in order to provide insights for Chinese scholars to carry out AI research. Methods AI related RCT researches were obtained by searching PubMed database. The Web of Science was used to obtain the publication year, citations, authors, institutions, and countries of included AI related RCT researches. The VOSviewer 1.6.17 software was used to extract the related information, generate visual cooperation network maps for the country, institutions and authors, and perform cluster analysis for keywords. The Cite Space 5.8.R3 software was used to analyze the burst citation references and keywords. Results A total of 1174 RCTs in AI field were included, with an average citation frequency of 36.09. The publication time was from 1989 to 2021, and the number of articles increased rapidly after 2007. Among them, the top 5 countries with the number of published articles were the United States(37.22%, 437 papers), Italy(10.90%, 128 papers), South Korea(8.86%, 104 papers), Germany(8.35%, 98 papers), China(7.84 %, 92 papers); the top 5 research institutions with the most published papers were Harvard University(2.98%, 35 papers), Yonsei University(2.73%, 32 papers), Northwestern University(2.21%, 26 papers), Massachusetts Institute of Technology(2.13%, 25 papers), Stanford University(1.96%, 23 papers), and the top 5 authors were Krebs(22 papers, Massachusetts Institute of Technology, US), Calabro(11 papers, IRCCS Neural Center, Italy), Picelli(11 papers, University of Verona, Italy), Smania(11 papers, University of Verona, Italy), Lin(10 papers, Taiwan University, China). Insufficient cooperation between prolific authors, research institutions, countries. The main hot topics were the application of robot technology in treatment, the application of machine learning in disease diagnosis and management, and the application of AI in rehabilitation training. Combined with strongest citation burst, it was found that robot assistance and machine learning may be the current research hot topics. Conclusions AI has great application prospects in the medical field, and the number of AI related RCT medical research has increased rapidly in recent years. Although the developed countries are in the leading position in this field, the researchers and research institutions in China have shown great potential. At present, the cooperation between the authors, research institutions and countries conducting AI related RCT medical research is not close, and the research topic needs to be expanded.

关键词(KeyWords)： 人工智能;随机对照试验;研究现状;文献计量学
artificial intelligence;randomized controlled trial;research status;bibliometric analysis

Abstract:

Keywords:

基金项目(Foundation):

作者(Authors): 史纪元;田金徽;高亚;许建国;李峥;
SHI Jiyuan;TIAN Jinhui;GAO Ya;XU Jian'guo;LI Zheng;School of Nursing,Chinese Academy of Medical Sciences & Peking Union Medical College;Evidence-Based Medicine Center,Lanzhou University;Key Laboratory of Evidence-based Medicine and Knowledge Translation of Gansu Province,Lanzhou University;

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