Interpretable Dynamic Treatment Regimes

DOI10.1080/01621459.2017.1345743zbMath1409.62231arXiv1606.01472OpenAlexW2411613392WikidataQ91662244 ScholiaQ91662244MaRDI QIDQ3121178

Marie Davidian, Anastasios A. Tsiatis, Eric B. Laber, Yichi Zhang

Publication date: 20 March 2019

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1606.01472

zbMATH Keywords

interpretabilitydecision liststree-based methodsprecision medicinetreatment regimesresearch-practice gap

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items (16)

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Uses Software

• NNLS
• glmnet
• randomForest

Cites Work

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• Tree-based methods for individualized treatment regimes
• Reader reaction to “A robust method for estimating optimal treatment regimes” by Zhang et al. (2012)
• Estimating Individualized Treatment Rules Using Outcome Weighted Learning
• Optimal Dynamic Treatment Regimes
• Tackling Box-Constrained Optimization via a New Projected Quasi-Newton Approach
• Doubly robust learning for estimating individualized treatment with censored data
• Optimal Structural Nested Models for Optimal Sequential Decisions
• New Statistical Learning Methods for Estimating Optimal Dynamic Treatment Regimes
• Robust estimation of optimal dynamic treatment regimes for sequential treatment decisions

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