Reinforcement Learning for Finding Optimal Dynamic Treatment Regimes Using Observational Data

This Guide to Statistics and Methods provides an overview of using observational data and reinforcement learning strategies to develop dynamic treatment regimes for patients who are critically ill.

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Publication Details

Journal
JAMA
Published
2025-12-17
DOI
https://doi.org/10.1001/jama.2025.20541
Citations
1
Primary Topic
Sepsis Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
1.35
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article

Reinforcement Learning for Finding Optimal Dynamic Treatment Regimes Using Observational Data

Andrea Rotnitzky, Marco Carone
1 citations
JAMA
Sepsis Diagnosis and Treatment
1.35
article

Reinforcement Learning for Finding Optimal Dynamic Treatment Regimes Using Observational Data

Andrea Rotnitzky, Marco Carone
article en
1 citations

Abstract

This Guide to Statistics and Methods provides an overview of using observational data and reinforcement learning strategies to develop dynamic treatment regimes for patients who are critically ill.

JAMAVol. 335(3)
University of Washington (US)
Openalex Percentile: Top 13%
Sepsis Diagnosis and Treatment
1.35
DOISourceOpenAlex
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Reinforcement Learning for Finding Optimal Dynamic Treatment Regimes Using Observational Data — Andrea Rotnitzky, Marco Carone · JAMA (2025) | TGRS Research Map | TGRS