Depth of Anesthesia Monitoring and Artificial Intelligence

Abstract

Purpose of Review This review aims to analyse, reflect, and elucidate on the evolution, basic knowledge, current advancements, prospects, and hurdles of using artificial intelligence in monitoring the depth of anesthesia, an intricate process that is crucial for ensuring patient safety and comfort but is influenced by numerous unpredictable variables in the operating room. Recent Findings Recent studies have demonstrated the effectiveness of using multiple electroencephalogram-based features along with other clinical parameters and artificial intelligence in order to accurately monitor and assess the depth of anesthesia, as well as to distinguish between different anesthetic states. In addition, artificial intelligence has been successfully integrated into monitoring the depth of anesthesia in a real-time and accurate manner. Summary This review explores the integration of Artificial Intelligence in depth of anesthesia monitoring, tracing its evolution from traditional methods to advanced AI-powered technologies. It examines several techniques highlighting their contributions to improving accuracy and patient safety. Challenges including data quality, interpretability, and ethical considerations are addressed, emphasizing the need for education, regulatory frameworks, and ongoing research. Despite hurdles, Artificial Intelligence holds promise for revolutionizing anesthesia care, contingent upon collaboration between human expertise and computational intelligence.