Artificial Intelligence in Anesthesia: Enhancing Precision, Efficiency, and Patient Outcomes

Abstract

Anesthesia has undergone significant advancements, from its early use in the 1800s to today’s sophisticated practices that ensure patient safety and comfort during medical procedures. As healthcare evolves, artificial intelligence (AI) is emerging as a transformative force in anesthesia, enhancing patient care, optimizing procedures, and improving outcomes. This review explores the integration of AI in anesthesia, covering its historical context, key principles like machine learning and deep learning, and the applications of AI across preoperative, intraoperative, and postoperative phases. The review highlights AI’s role in predictive modeling, personalized anesthesia planning, real-time monitoring, and rehabilitation. Furthermore, it discusses the challenges of data security, algorithm bias, and ethical concerns in AI implementation, as well as its impact on the future of anesthesia practice and education. By examining current advancements and potential future trends, this article provides insights into how AI can reshape anesthesia and healthcare delivery, emphasizing the need for collaboration and education to fully harness its benefits.