In recent years, research on artificial intelligence in joint diseases has become an increasingly popular field. This study aimed to investigate the global status and trends in this field and to identify research trends and hotspots in the application of artificial intelligence to joint diseases, thereby providing better guidance for clinical practice and scientific research. Research articles related to artificial intelligence in joint diseases were retrieved from the Science Citation Index Expanded (SCI-E) of Web of Science from January 01, 2006 to March 02, 2026. Bibliometric analysis was used to analyze and index the source data. VOSviewer software was used for bibliographic coupling, co-authorship, co-citation, and co-occurrence analyses to analyze publication trends in research on artificial intelligence in joint diseases. A total of 785 publications were included. Globally, research interest and the number of publications related to this field increased annually. The United States made the greatest contribution to global research, received the most citations, and had the highest h-index. JOURNAL OF ARTHROPLASTY had the largest number of publications. Shanghai Second Medical University, Johns Hopkins University School of Medicine, Perelman School of Medicine at the University of Pennsylvania, Johns Hopkins Medicine, and Perelman School of Medicine at the University of Pennsylvania were the institutions making the greatest contributions. Global bibliometric trends indicate that research output at the intersection of artificial intelligence and joint diseases will continue to increase. The United States remains in the leading tier by virtue of its total publication output and institutional innovation capacity, and is the most important contributor to global research in this field. Current research is highly concentrated on AI-enabled precision diagnosis and treatment of joint diseases and perioperative prognostic risk management. This direction has substantial potential for continued expansion and may become a core frontier hotspot in the medium to long term.

Xiangsen Xu, Tao Wu, Tianhao Sun, Pengfei Han, Yunfeng Xu. Global Research Trends in Artificial Intelligence for Joint Diseases: A Bibliometric and Visualization Study. Frontiers in Medical Science Research (2026), Vol. 8, Issue 5: 23-33. https://doi.org/10.25236/FMSR.2026.080503.

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