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Deep Reinforcement Learning for Dynamic Treatment Regimes on Medical Registry Data

In this paper, we propose the first deep reinforcement learning framework to estimate the optimal Dynamic Treatment Regimes from observational medical data. This framework is more flexible and adaptive for high dimensional action and state spaces than existing reinforcement learning methods to model...

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Bibliografiske detaljer
Udgivet i:Healthc Inform
Main Authors: Liu, Ying, Logan, Brent, Liu, Ning, Xu, Zhiyuan, Tang, Jian, Wang, Yanzhi
Format: Artigo
Sprog:Inglês
Udgivet: 2017
Fag:
Online adgang:https://ncbi.nlm.nih.gov/pmc/articles/PMC5856473/
https://ncbi.nlm.nih.gov/pubmed/29556119
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/ICHI.2017.45
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