An Explainable Deep Reinforcement Learning Model for Optimizing Warfarin Maintenance Dosing Using Policy Distillation and Action Forging

An explainable deep reinforcement learning model is proposed to optimize warfarin maintenance dosing by combining Proximal Policy Optimization, Policy Distillation, and novel "Action Forging" techniques to achieve a dosing protocol that is easy to understand and deploy while outperforming baseline dosing algorithms.