Artificial Intelligence in Anesthesiology: transforming perioperative monitoring and decision-making

Abstract

Artificial Intelligence (AI) has established itself as a promising tool in anesthesiology, enabling advances in continuous monitoring and decision-making during the perioperative period. The application of machine learning algorithms and artificial neural networks allows real-time analysis of multiple physiological parameters, contributing to greater precision in anesthetic administration, early identification of complications, and personalized patient care. Consequently, AI has the potential to enhance both the safety and efficiency of anesthetic procedures. This study consists of a narrative literature review, aiming to synthesize the major technological advances of AI in anesthesiology, discuss its benefits and challenges, and explore its clinical implications. The applications of AI in data-driven anesthesia personalization, prediction and mitigation of perioperative complications, and clinical decision support were analyzed. Additionally, ethical considerations and technical limitations associated with the implementation of these systems were addressed. The advancements of AI in anesthesiology demonstrate a significant impact on improving patient safety and clinical efficiency. However, its full adoption requires rigorous validation, careful regulation, and proper training of healthcare professionals. AI should be viewed as a complement to the expertise of anesthesiologists, assisting in the analysis of complex data and enabling a more precise and personalized approach. The synergy between technological innovation and clinical judgment represents the future of modern anesthesiology.