An Explainable Deep Reinforcement Learning Model for Warfarin Maintenance Dosing Using Policy Distillation and Action Forging
Deep Reinforcement Learning is an effective tool for drug dosing for chronic condition management. However, the final protocol is generally a black box without any justification for its prescribed doses. This paper addresses this issue by proposing an explainable dosing protocol for warfarin using a Proximal Policy Optimization method combined with Policy Distillation. We introduce Action Forging as an effective tool to achieve explainability. Our focus is on the maintenance dosing protocol. Results show that the final model is as easy to understand and deploy as the current dosing protocols and outperforms the baseline dosing algorithms.
Code (0)
등록된 구현이 없습니다.
Tasks
Deep Reinforcement LearningManagementMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Optimizing Warfarin Dosing using Deep Reinforcement Learning
Warfarin is a widely used anticoagulant, and has a narrow therapeutic range. Dosing of warfarin should be individualized, since slight overdosing or underdosing can have catastrophic or even fatal consequences. Despite m…
Deep Reinforcement Learningreinforcement-learningReinforcement LearningReinforcement Learning (RL)Evaluating the Effect of Longitudinal Dose and INR Data on Maintenance Warfarin Dose Predictions
Warfarin, a commonly prescribed drug to prevent blood clots, has a highly variable individual response. Determining a maintenance warfarin dose that achieves a therapeutic blood clotting time, as measured by the internat…
Estimate the Warfarin Dose by Ensemble of Machine Learning Algorithms
Warfarin dosing remains challenging due to narrow therapeutic index and highly individual variability. Incorrect warfarin dosing is associated with devastating adverse events. Remarkable efforts have been made to develop…
BIG-bench Machine LearningOptimizing Warfarin Dosing Using Contextual Bandit: An Offline Policy Learning and Evaluation Method
Warfarin, an anticoagulant medication, is formulated to prevent and address conditions associated with abnormal blood clotting, making it one of the most prescribed drugs globally. However, determining the suitable dosag…
Decision MakingA Computer-Aided System for Determining the Application Range of a Warfarin Clinical Dosing Algorithm Using Support Vector Machines with a Polynomial Kernel Function
Determining the optimal initial dose for warfarin is a critically important task. Several factors have an impact on the therapeutic dose for individual patients, such as patients' physical attributes (Age, Height, etc.),…
General Classification