Evaluating the use of generalized dynamic weighted ordinary least squares for individualized HIV treatment strategies
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Publication:6179138
DOI10.1214/22-AOAS1726arXiv2109.01218MaRDI QIDQ6179138
Laura Villain, Rodolphe Thiébaut, Erica E. M. Moodie, Larry Dong
Publication date: 16 January 2024
Published in: The Annals of Applied Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2109.01218
longitudinal dataHIVindividualized treatment ruleprecision medicinedynamic treatment regimeadaptive treatment strategy
Cites Work
- Unnamed Item
- Statistical methods for dynamic treatment regimes. Reinforcement learning, causal inference, and personalized medicine
- Bootstrap methods: another look at the jackknife
- Tree-based reinforcement learning for estimating optimal dynamic treatment regimes
- Modeling CD4\(^+\) T cells dynamics in HIV-infected patients receiving repeated cycles of exogenous Interleukin 7
- Controlling IL-7 injections in HIV-infected patients
- Doubly-robust dynamic treatment regimen estimation via weighted least squares
- Q-learning for estimating optimal dynamic treatment rules from observational data
- Using Joint Utilities of the Times to Response and Toxicity to Adaptively Optimize Schedule–Dose Regimes
- The central role of the propensity score in observational studies for causal effects
- Treatment Monitoring of HIV‐Infected Patients based on Mechanistic Models
- Estimating Optimal Dynamic Treatment Regimes With Survival Outcomes
- Multi-Armed Angle-Based Direct Learning for Estimating Optimal Individualized Treatment Rules With Various Outcomes
- Optimal Structural Nested Models for Optimal Sequential Decisions
- Doubly Robust Estimation of Optimal Dosing Strategies
- Multicategory Angle-Based Learning for Estimating Optimal Dynamic Treatment Regimes With Censored Data
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