Artificial Intelligence in Pediatric Anesthesia

Abstract

This text explores the integration of artificial intelligence (AI) into pediatric anesthesiology, highlighting its potential to enhance safety, efficiency, and decision-making throughout the perioperative period. It addresses the unique challenges of pediatric anesthesia, including physiologic differences, limited communication, and congenital conditions. AI applications are being developed for operating room management, airway assessment, intraoperative monitoring, and postoperative care. These tools show promise in predicting surgical cancellations, difficult airways, hypoxia, and optimal intubation parameters. However, pediatric-specific data and tailored algorithms are essential, as adult models are often unsuitable. The study underscores the need for rigorous research and ethical application.

Keywords: Airway management; Artificial intelligence (AI); Machine learning (ML); Pediatric anesthesiology; Perioperative decision support.