Xie Yaojue, Zhai Yuansheng, Lu Guihua
Yangjiang Bainian Yanshen Medical Technology Co., Ltd., Yangjiang, China.
Department of Cardiology, Heart Center, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Front Med (Lausanne). 2025 Jan 15;11:1505692. doi: 10.3389/fmed.2024.1505692. eCollection 2024.
In recent years, the development of artificial intelligence (AI) technologies, including machine learning, deep learning, and large language models, has significantly supported clinical work. Concurrently, the integration of artificial intelligence with the medical field has garnered increasing attention from medical experts. This study undertakes a dynamic and longitudinal bibliometric analysis of AI publications within the healthcare sector over the past three decades to investigate the current status and trends of the fusion between medicine and artificial intelligence.
Following a search on the Web of Science, researchers retrieved all reviews and original articles concerning artificial intelligence in healthcare published between January 1993 and December 2023. The analysis employed Bibliometrix, Biblioshiny, and Microsoft Excel, incorporating the bibliometrix R package for data mining and analysis, and visualized the observed trends in bibliometrics.
A total of 22,950 documents were collected in this study. From 1993 to 2023, there was a discernible upward trajectory in scientific output within bibliometrics. The United States and China emerged as primary contributors to medical artificial intelligence research, with Harvard University leading in publication volume among institutions. Notably, the rapid expansion of emerging topics such as COVID-19 and new drug discovery in recent years is noteworthy. Furthermore, the top five most cited papers in 2023 were all pertinent to the theme of ChatGPT.
This study reveals a sustained explosive growth trend in AI technologies within the healthcare sector in recent years, with increasingly profound applications in medicine. Additionally, medical artificial intelligence research is dynamically evolving with the advent of new technologies. Moving forward, concerted efforts to bolster international collaboration and enhance comprehension and utilization of AI technologies are imperative for fostering novel innovations in healthcare.
近年来，包括机器学习、深度学习和大语言模型在内的人工智能（AI）技术发展显著支持了临床工作。与此同时，人工智能与医学领域的融合日益受到医学专家的关注。本研究对过去三十年医疗保健领域内人工智能出版物进行了动态的纵向文献计量分析，以调查医学与人工智能融合的现状和趋势。
在科学网进行检索后，研究人员检索了1993年1月至2023年12月间发表的所有关于医疗保健领域人工智能的综述和原创文章。分析采用了Bibliometrix、Biblioshiny和Microsoft Excel，结合用于数据挖掘和分析的Bibliometrix R包，并对文献计量学中观察到的趋势进行了可视化处理。
本研究共收集到22950篇文献。从1993年到2023年，文献计量学的科学产出呈现出明显的上升趋势。美国和中国是医学人工智能研究的主要贡献者，哈佛大学在机构发表量方面领先。值得注意的是，近年来诸如COVID-19和新药发现等新兴主题的迅速扩展。此外，2023年被引用次数最多的五篇论文均与ChatGPT主题相关。
本研究揭示了近年来医疗保健领域人工智能技术持续的爆发式增长趋势，在医学中的应用越来越深入。此外，随着新技术的出现，医学人工智能研究也在动态发展。展望未来，加强国际合作以及提高对人工智能技术的理解和利用的共同努力对于促进医疗保健领域的新创新至关重要。
