Why the study?
Artificial intelligence has potential to transform perioperative medicine by leveraging complex datasets to predict risks and optimise patient management, but research trends and hotspots needed analysis.
Research on artificial intelligence in perioperative medicine is rapidly expanding, particularly in risk prediction and intraoperative monitoring, though it currently lacks extensive international collaboration.
Rapid post-2018 AI perioperative research growth warrants clinician awareness of emerging tools; leaves open the need for international collaboration to validate applications.
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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Chan et al. (2025) studied this question.
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