Learning and Assessing Optimal Dynamic Treatment Regimes Through Cooperative Imitation Learning

Learning and Assessing Optimal Dynamic Treatment Regimes Through Cooperative Imitation Learning

Dynamic Treatment Regimes (DTRs) are sets of sequential decision rules that can be adapted over time to treat patients with a specific pathology. DTR consists of alternative treatment paths and any of these treatments can be adapted depending on the patient's characteristics. Reinforcement Lear...

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Bibliographic Details
Main Authors: Syed Ihtesham Hussain Shah, Antonio Coronato, Muddasar Naeem, Giuseppe De Pietro
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Inverse reinforcement learning
imitation learning
dynamic treatment regime
reinforcement learning
cooperative imitation learning
Markov decision process
Online Access:https://ieeexplore.ieee.org/document/9837927/

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