已发表论文

21世纪以来人工智能在肌肉骨骼疾病中的科学计量学世界观

 

Authors Cao S , Wei Y, Yue Y, Wang D, Xiong A , Zeng H

Received 7 May 2024

Accepted for publication 26 June 2024

Published 9 July 2024 Volume 2024:17 Pages 3193—3211

DOI https://doi.org/10.2147/JMDH.S477219

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 3

Editor who approved publication: Dr Scott Fraser

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 work

Correspondence: Ao Xiong; Hui Zeng, Email xiongao@189.cn; zenghui@pkuszh.com

Purpose: 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