Minerva Anestesiologica 2020 Dec 10

DOI: 10.23736/S0375-9393.20.14999-X

Copyright © 2020 EDIZIONI MINERVA MEDICA

lingua: Inglese

Artificial intelligence and perioperative medicine

Elena G. BIGNAMI ¹ ✉, Federico COZZANI ², Paolo DEL RIO ², Valentina BELLINI ¹

¹ Unit of Anesthesiology, Division of Critical Care and Pain Medicine, Department of Medicine and Surgery, University of Parma, Parma, Italy; ² General Surgery Unit, Parma University Hospital, Parma, Italy

Perioperative medicine is a patient-centered, multidisciplinary and integrated clinical practice that starts from the moment of contemplation of surgery until full recovery. Every perioperative phase (preoperative, intraoperative and postoperative) has to be studied and planned in order to optimize the entire patient management. Perioperative optimization does not only concern a short-term outcome improvement, but it has also a strong impact on long term survival. Clinical cases variability leads to the collection and analysis of a huge amount of different data, coming from multiple sources, making perioperative management standardization very difficult. Artificial Intelligence (AI) can play a primary role in this challenge, helping human mind in perioperative practice planning and decision-making process. AI refers to the ability of a computer system to perform functions and reasoning typical of the human mind; Machine Learning (ML) could play a fundamental role in pre-surgical planning, during intraoperative phase and postoperative management. Perioperative medicine is the cornerstone of surgical patient management and the tools deriving from the application of AI seem very promising as a support in optimizing the management of each individual patient. Despite the increasing help that will derive from the use of AI tools, the uniqueness of the patient and the particularity of each individual clinical case will always keep the role of the human mind central in clinical and perioperative management. The role of the physician, who must analyse the outputs provided by AI by following his own experience and knowledge, remains and will always be essential.

KEY WORDS: Artificial Intelligence; Perioperative medicine; Machine learning; Perioperative management; Risk assessment; Predictive value