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Updated: May 6, 2026
Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
Published on: October 24, 2019
Quantitative analysis of studies that use artificial intelligence on spinal diseases: A bibliometric analysis
Fengyuan Liu1, Chunyun Li2, Yong Liu2
1Department of Clinical Medicine, Hunan Normal University Health Science Center, Changsha, Hunan, China.
Objective:
This study aimed to evaluate the current research progress and future research directions of artificial intelligence in spinal diseases through a bibliometric analysis.
Methods:
Publications regarding spinal diseases and artificial intelligence published from 2006 to 2025 were extracted from the Web of Science Core Collection (WOSCC). Subsequently, a bibliometric analysis of these publications was conducted using CiteSpace, VOSviewer, and Bibliometrix Online Analysis Platform.
Results:
A total of 734 papers were included in the study. The annual publication numbers are on the rise. The USA (267 papers) and Beijing Jishuitan Hospital (24 papers) were identified as the most productive country and institution, respectively. Tian, Wei (25 papers) is the most productive author. "Spine" (49 publications) is the most productive journal. "Machine Learning" was the most cited keyword, with high-frequency keywords such as "Artificial Intelligence," "Robotic Surgery," "Deep learning," "Virtual Reality," and "predictive modeling" signaling hot topics in this field.
Conclusions:
There are increasingly many papers on artificial intelligence in spinal diseases. However, cooperation between institutions in various countries needs to be strengthened. In addition, this study summarized the research focus of artificial intelligence in spinal disorders as accurate diagnosis, robot-assisted surgery, and prognosis prediction, providing researchers with future research directions.
