A hierarchical reinforcement learning and predictive control framework for automated multi-variable anesthesia
BACKGROUND AND OBJECTIVE: Automated multi-variable anesthesia must balance conflicting objectives amid patient variability, safety constraints, and partial observability. The state-of-the-art robust approach uses a Genetic Algorithm (GA) to optimize Generalized Predictive Control (GPC) parameters across a population, b...
Sara Hosseinirad, Manuela Merlo, Francesco Trovò et al.
· Computers in Biology and Med... · 0 citations