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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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| Publicado no: | Healthc Inform |
|---|---|
| Main Authors: | , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2017
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| Assuntos: | |
| Acesso em linha: | 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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