中医教育2026，Vol.45Issue(8)：24-31,8.DOI:10.3969/j.issn.1003-305X.2026.08.246
基于CiteSpace的人工智能赋能医学教育研究热点及趋势可视化分析
CiteSpace-based visualization analysis of research hotspots and trends in artificial intelligence-enabled medical education
王龙 1任玉梅 1韩姗姗 1李向峰 1张霞 1任献青 1丁樱1
作者信息
- 1. 河南中医药大学第一附属医院儿科医院 郑州 450000||河南中医药大学儿科医学院 郑州 450000
- 折叠
摘要
Abstract
Objective To systematically analyze the current research status,hotspots,and evolutionary trends in artificial intelligence(AI)-enabled medical education,and to provide reference for the digital transformation of medical education.Methods Literature related to AI-enabled medical education was retrieved from CNKI,Wanfang Data,VIP,and the Chinese Biomedical Literature Service System(CBM).CiteSpace 6.4.R2 was used to conduct visual analyses of publication trends,author and institutional collaboration networks,keyword co-occurrence,keyword clustering,timeline distribution,and keyword bursts.Results The number of publications in this field showed an overall upward trend.The research hotspots mainly focused on five core directions:the application of AI technologies in medical education,teaching reform in the context of New Medicine,empowerment through virtual simulation and virtual reality technologies,integration with fields such as nursing education,and innovation in medical talent cultivation models.The research frontiers included technology application,specific application scenarios,and ethical risk regulation,with clinical teaching remaining a continuously prominent research hotspot.Conclusion AI-enabled medical education has become a core research direction in medical education reform.Future research should further strengthen interdisciplinary and inter-institutional collaboration,improve the evaluation system and ethical norms for technology application,promote the organic integration of AI and medical education,and support the cultivation of high-quality medical talents.关键词
人工智能/医学教育/可视化分析/新医科/教学改革Key words
artificial intelligence/medical education/visualization analysis/New Medicine/teaching reform分类
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王龙,任玉梅,韩姗姗,李向峰,张霞,任献青,丁樱..基于CiteSpace的人工智能赋能医学教育研究热点及趋势可视化分析[J].中医教育,2026,45(8):24-31,8.
