ARTIFICIAL INTELLIGENCE IN VETERINARY ANESTHESIOLOGY: APPLICATIONS IN RISK PREDICTION, INTRAOPERATIVE MONITORING, AND ANESTHETIC SAFETY IN LARGE AND SMALL ANIMALS

Abstract

Artificial Intelligence (AI) has promoted significant advances in veterinary medicine, particularly in anesthesiology, contributing to greater accuracy in clinical assessment, intraoperative monitoring, and prevention of anesthetic complications. This chapter aims to analyze the main applications of AI in veterinary anesthesiology for both large and small animals, highlighting its potential in risk prediction, real-time physiological monitoring, and enhancement of anesthetic safety. The methodology consisted of a narrative literature review based on scientific articles published in national and international databases, specialized books, and technical documents related to veterinary medicine, artificial intelligence, and anesthesiology. The findings indicate that machine learning algorithms and intelligent systems can process large volumes of clinical data, identify patterns associated with anesthetic complications, and support decision-making during surgical procedures. Furthermore, AI-based tools enable the early detection of cardiovascular, respiratory, and metabolic changes, allowing faster and more effective interventions. It is concluded that the integration of Artificial Intelligence into veterinary anesthesiology represents a promising strategy to improve patient safety, optimize anesthetic protocols, and support veterinary professionals, although challenges related to clinical validation and technological implementation still need to be addressed.