IOT-Based Anesthesia Machine Control using Machine Learning

This study investigates the use of machine learning to customize and optimize anesthesia treatment, addressing the issue of patient variability in reaction to anesthesia .Machine Learning algorithms will process large datasets containing patient information, medical history, and surgical specifies .These findings will be utilized to create tailored anesthetic prediction algorithms that adjust medication regimes to specific patient features. The study aims to reduce the hazards associated with unpredictable patient responses. Understanding individual characteristics through trained algorithms allows for safer and more effective anesthetic regimes, potentially leading to better patient outcomes and recovery. Throughout surgery, systems will continuously assess data, modifying forecasts to reflect changing conditions. This enhances patient safety and provides dynamic decision support for healthcare professionals throughout the procedure. Seamless integration with existing healthcare information systems and electronic health records is crucial.