摘要
目的:分析人工智能(AI)医学技术研究与开发的聚焦领域与趋势。方法:以多检索词组合、多重检索策略对中国知网、万方数据平台及维普期刊整合平台进行文献检索(2008-2017年);运用文献计量学、书目信息共现分析系统(BICOMB)进行文献计量,构建高频关键词词篇矩阵,用图形聚类工具包(g Cluto)进行双聚类可视化分析。结果:检索共获得样本文献505篇,文献量在2015年开始攀升,在2017年达到128篇,是2008年的2倍;截取高频关键词97个,聚类分析得5类:(1)基于医学图像的AI影像学、病理学辅助诊断与放疗图像配准和靶区勾画;(2)医疗机器人与计算机辅助外科;(3)AI算法、模式的知识体系与在生理信号分析、脑神经科学等方面的应用研究;(4)AI技术与慢病管理、健康管理和医院管理;(5)数据挖掘等AI技术在临床决策系统、医学专家系统构建及药物发掘上的应用。结论:AI医学技术文献在近3年中呈攀升趋势,表明处于一个非常活跃的AI医学技术研发时期,聚焦在5个技术热点。建议应从加强支撑体系建设、规范数据采集、有效利用大数据及开展基于卫生健康需求的卫生技术评估入手,促进AI产业发展,提高医疗健康服务水平。
Objective： To analyze the focus topics and trends of research and development on artificial intelligence（AI） medical technology. Methods： Using multiple retrieval words combination and multiple retrieval strategy, the literature retrieval（January 1,2008 to December 31, 2017） was carried out on China Knowledge Resource Integrated Database, Wanfang Data and VIP journal integration platform. Bibliographic item CO-occurrence matrix builder（BICOMB） were used to construct high frequency key words, and graphical clustering toolkit（g Cluto） for term paper cluster visualization analysis. Results： 505 articles were obtained. The number of literature began to rise in 2015 and reached 128 in 2017, which was 2 times in 2008; 97 high frequency key words were intercepted and 5 categories were analyzed by cluster analysis.（1）applications and research of assisted diagnosis of medical images, pathology, and radiotherapy target delineation based on AI imaging technology.（2）medical Robot and computer assisted surgery.（3）the knowledge system of AI algorithm and model and applications in physiological signal analysis and brain neuroscience;（4）AI technology and chronic disease management, health management, hospital management.（5）data mining and other AI technology and the construction of clinical decision-making system, medical expert system and application in drug discovery. Conclusion： The annual quantities of literature shows a rising trend in the past 3 years, shows that in a very active AI medical technology research and development period, and focuses on 5 technology hotspots. It is suggested that we should start with strengthening the construction of the support system, standardize the data collection and effectively use the large data and carry out the health technology assessment based on the medical and healthcare needs to promote the development of the AI industry in China and improve the level of medical health service.
作者
李志勇
李鹏伟
高小燕
孙湛
麻良
崔泽实
LI Zhi-yong;LI Peng-wei;GAO Xiao-yan(China Association of Medical Equipment,Beijing 100098,China)
出处
《中国医学装备》
2018年第7期136-145,共10页
China Medical Equipment
关键词
人工智能
医学技术
医学装备
文献计量学
Artificial intelligence
Medical technology
Medical device
Bibliometrics
作者简介
李志勇,男,（1976-）,硕士,高级工程师,中国医学装备协会秘书长,研究方向：卫生事业管理与医学装备技术评估.;通信作者：zscui@cmu.edu.cn
