Key concepts in artificial intelligence for anesthesiologists: a literature review

Abstract

Artificial Intelligence (AI) is revolutionizing medical practice across various fields, including anesthesiology.Despite its potential, AI adoption in clinical settings faces challenges related to data robustness, result interpretation by anesthesiologists, and ethical issues around privacy and automated decision-making.This narrative review aims to provide anesthesiologists with an updated overview of AI applications in medical practice, empowering them to become active contributors to this transformation.With the widespread adoption of electronic health records and the availability of large-scale perioperative data, AI applications have rapidly evolved, offering the potential to make anesthetic management more personalized, predictive, and preventive.AI applications in anesthesiology span the perioperative period, from preoperative planning to postoperative care.Recent advances allow AI to assist in interpreting diagnostic tests, predicting complications, real-time monitoring, and supporting clinical decision-making.However, for anesthesiologists to use these tools effectively, they must possess a foundational understanding of AI, including its terminology, algorithms, validation methods, and the ethical and practical limitations of its use.This article seeks to guide readers in acquiring the necessary knowledge to become well-informed anesthesiologists capable of integrating AI into their practice efficiently.By fostering collaboration and understanding between anesthesiologists and AI technologies, we aim to drive meaningful advancements in anesthetic practice and improve patient outcomes.

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