Reinforcement Learning Versus Proportional–Integral–Derivative Control of Hypnosis in a Simulated Intraoperative Patient

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Reinforcement Learning in Healthcare: A Survey (2019, methodology): “ain physiological stability and lowering pains of patients Moore et al. [206], [207] Q() N/A N/A PK/PD model Achieving superior stability compared to a well-tuned PID controller. Moore et al. [208], [209] Q-learning N/A N/A PK/PD model Using the change of BIS as the state representation. Moore et al”
Reinforcement learning for closed-loop propofol anesthesia: a study in human volunteers (2014, methodology): “However, RL has no reported application to clinical control problems, with the exception of work leading to this study (Moore et al., 2011a,b, 2004).”
An Adaptive Neural Network Filter for Improved Patient State Estimation in Closed-Loop Anesthesia Control (2011, methodology): “In prior studies of reinforcement learning [5], we utilized the Schnider pharmacokinetic (PK) model [16] to describe the time-dependent distribution of propofol within”