A bibliometric analysis of perioperative medicine and artificial intelligence.
作者信息
Chan Luke Kar Man, Mao Brooke Perrin, Zhu Rebecca
机构信息
Department of Anaesthesia, Concord Repatriation General Hospital, Sydney, NSW, Australia.
Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia.
出版信息
J Perioper Pract. 2025 Mar 4:17504589251320811. doi: 10.1177/17504589251320811.
BACKGROUND
Artificial intelligence holds the potential to transform perioperative medicine by leveraging complex datasets to predict risks and optimise patient management in response to rising surgical volumes and patient complexity.
AIM
This bibliometric analysis aims to analyse trends, contributions, collaborations and research hotspots in artificial intelligence and perioperative medicine.
METHODS
A Scopus search on 11 October 2024 identified articles on artificial intelligence in perioperative medicine. Relevant peer-reviewed studies were screened by two reviewers, with a third resolving discrepancies. Data were analysed using VOSviewer, Biblioshiny and Microsoft Excel.
RESULTS
A total of 240 articles were included; 84% of articles were published after 2018, indicating rapid recent growth. The United States, China and Italy led contributions. Single-country publications comprised 76.6% of the dataset, reflecting limited international collaboration. Key research areas included perioperative risk prediction, intraoperative monitoring, blood management and echocardiography.
CONCLUSION
Artificial intelligence in perioperative medicine is rapidly advancing but requires increased international collaboration to fully realise its potential.
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