Artificial Intelligence in Orthopedics: Global Research Trends and Emerging Applications

Artificial intelligence (AI) has rapidly expanded across orthopedics, with applications spanning imaging analysis, preoperative planning, implant selection, outcome prediction, rehabilitation, and related clinical workflows. Despite rapid growth in the literature, the global research landscape remains incompletely characterized.

To characterize global research trends in AI applications in orthopedics, including publication growth, disciplinary distribution, authorship, journal patterns, geographic output, and thematic evolution.

The Web of Science Core Collection was searched for publications indexed from 1997 through June 16, 2026 using terms related to artificial intelligence and orthopedics. A total of 2,351 records were analyzed. VOSviewer was used for co-authorship, keyword co-occurrence, and co-citation network mapping.

Publication output increased sharply after 2016, with 97.9% of publications appearing from 2017 through the partial 2026 period. Output reached 636 publications in 2025. Computer Science, Interdisciplinary Applications (36.7%) and Health Care Sciences & Services (22.2%) were the leading Web of Science categories, whereas Orthopedics (4.2%) and Surgery (4.3%) represented smaller shares. Chen Y was the most prolific author with 30 publications (1.3%), and no single journal accounted for more than 1.8% of publications. Japan (33.1%) and South Korea (18.3%) led national output. Keyword mapping demonstrated three co-dominant hubs centered on artificial intelligence, machine learning, and deep learning, while co-citation analysis identified foundational clusters rooted largely in computer science methodology.

AI research in orthopedics has expanded rapidly and is increasingly interdisciplinary. The literature is broadly distributed across authors and journals, with no single dominant research group or publication venue. Emerging areas include large language models.