Bibliometrics of artificial intelligence applications in hepatobiliary surgery from 2014 to 2024

作者：Rujun Zheng, D X Li, Hao-Min Lin, Junfeng Wang, Yamei Luo, Yong Tang, Fan Li, Yue Hu, Song Su · 发表于：World Journal of Gastrointestinal Surgery · 年份：2025 · DOI：10.4240/wjgs.v17.i5.104728 · 被引用次数：3 · 研究领域：Artificial Intelligence in Healthcare and Education、Radiomics and Machine Learning in Medical Imaging、Surgical Simulation and Training

BACKGROUND In recent years, the rapid development of artificial intelligence (AI) in hepatobiliary surgery research has led to an increase in articles exploring its benefits. We performed a bibliometric analysis of AI applications in hepatobiliary surgery to better delineate the contemporary state of AI application in hepatobiliary surgery and potential future trajectories. AIM To provide clinical practitioners with a reliable reference point. It offers a detailed overview of the development of AI in hepatobiliary surgery by systematically examining the contributions of authors, countries, institutions, journals, and keywords in this domain over the last 10 years. METHODS The academic resources utilized in this study were obtained from the Web of Science Core Collection database. The search results were subsequently integrated and imported into CiteSpace and VOSviewer software for the purpose of visual analysis. RESULTS The study analyzed 2552 publications during 2014–2024. These publications collectively garnered 32 628 citations, averaging 15.66 citations per paper. The top contributor to this field was China. The USA had the highest citation count. The author with the highest citation count was Summers RM. In terms of the number of articles published, the leading journals were Medical Physics . Excluding the subject search terms, the most frequently used keywords included “classification”, “CT and “diagnosis”. CONCLUSION This bibliometric analysis indicates that research o...