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A bibliometric analysis of perioperative medicine and artificial intelligence
Luke Kar Man Chan1,2,3, Brooke Perrin Mao1,2, Rebecca Zhu4
1Department of Anaesthesia, Concord Repatriation General Hospital, Sydney, NSW, Australia.
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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