A bibliometric analysis of the global research landscape on artificial intelligence applications in clinical medicine (2010–2025)

Objective In the digital era, artificial intelligence (AI) is increasingly used in clinical medicine. To investigate this trend, this study uses bibliometric methods to systematically review the literature on AI applications in clinical medicine from 2010 to 2025, aiming to reveal the global landscape of development. Methods This study employs bibliometric analysis methods based on the Web of Science Core Collection database, utilizing software such as Microsoft Office Excel 2023, Origin, VOSviewer, CiteSpace, and Bibliometrix to analyze the selected literature and identify research trends and hotspots in the application of AI within clinical medicine. Results A total of 2,872 literature articles on AI applications in clinical medicine were included in the analysis. Since 2017, publication volume has increased significantly. Researchers from 114 countries contributed to this field. The United States produced the highest number of articles and led in international collaborations. In total, 1,000 institutions were engaged in AI clinical medicine research, with Harvard Medical School having the highest output (n = 85). 19,537 researchers contributed to the publication of the research report. Arman Rahmim from the University of British Columbia was the most prolific (n = 12), maintaining high productivity between 2020 and 2022. The fields of medicine, general medicine, and internal medicine dominated participation in AI clinical applications. Biomedical sciences showed the highest level of involvement (n = 798). Currently, AI, classification, and prediction studies are at the forefront of AI clinical applications. In 2023, the emergence of ChatGPT, a large language model, brought this technology to the forefront. Conclusion AI fosters rapid growth in global research within clinical medicine. This expansion is driven by technological innovation and spreads across all areas of healthcare. Large language models, such as ChatGPT, have initiated a new growth phase in this field. Their integration with clinical scenarios is accelerating intelligent and convergent advancements.