A Scientometric Worldview of Artificial Intelligence in Musculoskeletal Diseases Since the 21st Century

Siyang Cao,1– 3,* Yihao Wei,1– 3,* Yaohang Yue,1– 3,* Deli Wang,1– 3 Ao Xiong,1– 3 Hui Zeng1– 3 1National & Local Joint Engineering Research Centre of Orthopaedic Biomaterials, Peking University Shenzhen Hospital, Shenzhen, Guangdong, People’s Republic of China; 2Shenzhen Key Laboratory of Orthopaedic Diseases and Biomaterials Research, Peking University Shenzhen Hospital, Shenzhen, Guangdong, People’s Republic of China; 3Department of Bone & Joint Surgery, Peking University Shenzhen Hospital, Shenzhen, Guangdong, People’s Republic of China*These authors contributed equally to this workCorrespondence: Ao Xiong; Hui Zeng, Email xiongao@189.cn; zenghui@pkuszh.comPurpose: Over the past 24 years, significant advancements have been made in applying artificial intelligence (AI) to musculoskeletal (MSK) diseases. However, there is a lack of analytical and descriptive investigations on the trajectory, essential research directions, current research scenario, pivotal focuses, and future perspectives. This research aims to provide a thorough update on the progress in AI for MSK diseases over the last 24 years.Methods: Data from the Web of Science database, covering January 1, 2000, to March 1, 2024, was analyzed. Using advanced analytical tools, we conducted comprehensive scientometric and visual analyses.Results: The findings highlight the predominant influence of the USA, which accounts for 28.53% of the total publications and plays a key role in shaping research in this field. Notable productivity was seen at institutions such as the University of California, San Francisco, Harvard Medical School, and Seoul National University. Valentina Pedoia is identified as the most prolific contributor. Scientific Reports had the highest number of publications in this area. The five most significant diseases are joint diseases, bone fractures, bone tumors, cartilage diseases, and spondylitis.Conclusion: This comprehensive scientometric assessment benefits both experienced researchers and newcomers, providing quick access to essential information and fostering the development of innovative concepts in this field. Keywords: artificial intelligence, musculoskeletal diseases, scientometrics, data visualization, global scientific frontiers