Artificial Intelligence for Perioperative Medicine in Anesthesia: Present State and Future Perspectives of AI in Anesthesiology

Abstract

The latest development of artificial intelligence has recast perioperative medicine, especially anesthesia. This review combined the knowledge gained from various studies of artificial intelligence applications in the development of models on risk stratification, event prediction, and intensive care in the perioperative context. Further, external validation of these models was performed to prove their reliability. Integration of electronic health records will offer real-time support for anesthesiologists to make better decisions and predict complications. This review has been performed with a systematic search through databases such as PubMed, Journal of Anesthesia & Analgesia, Open Journal of Anesthesiology, MDPI Open Access Journal, National Library of Medicine, ResearchGate, and Korean Journal of Anesthesiology, by using appropriate keywords relevant to “AI in Anesthesiology.” Google Scholar was the primary tool. Inclusion criteria considered relevance, peer-reviewed status, and publication credibility. Data synthesis focused on current AI applications, challenges, future perspectives, and case studies. Quality assessment ensured reliability, and the iterative process allowed for continuous updates. Thorough documentation and citation practices maintained transparency. This approach aims to offer a concise, comprehensive analysis of AI’s role in anesthesiology’s perioperative landscape. The narrative review deals with the transformational role of AI in clinical anesthesia, ranging from machine learning applications to closed loops and robotic precision. Against all the enormous potential, a few challenges are discussed: ethical ones and those related to technology adoption. This changing role of the anesthesiologist in expanded perioperative care is powered by artificial intelligence for safer practices. This scoping review examines emerging uses of artificial intelligence in anesthesiology and reviews the impact on clinical care. From perioperative support and outpatient pain management in the case of anesthesiologists to the technology’s limitations, which very well place the onus back on the clinicians with respect to developing artificial intelligence itself – the implications all bear witness that artificial intelligence stands forth as the pivotal force upon which progresses in perioperative practices revolve.

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