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Minerva Anestesiologica 2022 September;88(9):729-34

DOI: 10.23736/S0375-9393.21.16241-8

Copyright © 2021 EDIZIONI MINERVA MEDICA

language: English

Artificial intelligence and telemedicine in anesthesia: potential and problems

Valentina BELLINI 1, Marina VALENTE 2, Antonio V. GADDI 3, Paolo PELOSI 4, 5, Elena BIGNAMI 1

1 Unit of Anesthesiology, Division of Critical Care and Pain Medicine, Department of Medicine and Surgery, University of Parma, Parma, Italy; 2 Unit of General Surgery, Department of Medicine and Surgery, University of Parma, Parma, Italy; 3 Center for Metabolic Diseases and Atherosclerosis, University of Bologna, Bologna, Italy; 4 Department of Anesthesia and Intensive Care, IRCCS San Martino University Hospital, University of Genoa, Genoa, Italy; 5 Department of Surgical Sciences and Integrated Diagnostics (DISC), University of Genoa, Genoa, Italy



The application of novel technologies like artificial intelligence (AI), machine learning (ML) and telemedicine in anesthesiology could play a role in transforming the future of health care. In the present review we discuss the current applications of AI and telemedicine in anesthesiology and perioperative care, exploring their potential influence and the possible hurdles. AI technologies have the potential to deeply impact all phases of perioperative care from accurate risk prediction to operating room organization, leading to increased cost-effective care quality and better outcomes. Telemedicine is reported as a successful mean within the anesthetic pathway, including preoperative evaluation, remote patient monitoring, and postoperative care. The utilization of AI and telemedicine is promising encouraging results in perioperative management, nevertheless several hurdles remain to be overcome before these tools could be integrated in our daily practice. AI models and telemedicine can significantly influence all phases of perioperative care, helping physicians in the development of precision medicine.


KEY WORDS: Perioperative medicine; Artificial intelligence; Machine learning; Operating rooms; Telemedicine

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