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Dynamic treatment regimes (DTRs) have received an increasing interest in recent years. DTRs are sequences of treatment decision rules tailored to patient-level information. The main goal of the DTR study is to identify an optimal DTR, a…

统计方法学 · 统计学 2024-04-09 Dan Liu , Wenqing He

The study of precision medicine involves dynamic treatment regimes (DTRs), which are sequences of treatment decision rules recommended by taking patient-level information as input. The primary goal of the DTR study is to identify an optimal…

统计方法学 · 统计学 2024-12-11 Dan Liu , Wenqing He

A dynamic treatment regimen (DTR) is a set of decision rules to personalize treatments for an individual using their medical history. The Q-learning-based Q-shared algorithm has been used to develop DTRs that involve decision rules shared…

机器学习 · 统计学 2024-12-05 Palash Ghosh , Xinru Wang , Trikay Nalamada , Shruti Agarwal , Maria Jahja , Bibhas Chakraborty

Dynamic treatment regimens (DTRs) aim at tailoring individualized sequential treatment rules that maximize cumulative beneficial outcomes by accommodating patients' heterogeneity in decision-making. For many chronic diseases including type…

统计方法学 · 统计学 2024-04-23 Mochuan Liu , Yuanjia Wang , Haoda Fu , Donglin Zeng

Health policy decisions regarding patient treatment strategies require consideration of both treatment effectiveness and cost. Optimizing treatment rules with respect to effectiveness may result in prohibitively expensive strategies; on the…

统计方法学 · 统计学 2021-10-20 Nicholas Illenberger , Andrew J. Spieker , Nandita Mitra

Dynamic treatment regimes (DTRs) formalize medical decision-making as a sequence of rules for different stages, mapping patient-level information to recommended treatments. In practice, estimating an optimal DTR using observational data…

统计方法学 · 统计学 2024-12-11 Jian Sun , Bo Fu , Li Su

Dynamic treatment regimes (DTR) are sequential decision rules corresponding to several stages of intervention. Each rule maps patients' covariates to optional treatments. The optimal dynamic treatment regime is the one that maximizes the…

统计方法学 · 统计学 2023-10-10 Zhishuai Liu , Zishu Zhan , Jian Liu , Danhui Yi , Cunjie Lin , Yufei Yang

A dynamic treatment regimen (DTR) is a pre-specified sequence of decision rules which maps baseline or time-varying measurements on an individual to a recommended intervention or set of interventions. Sequential multiple assignment…

统计方法学 · 统计学 2019-10-23 Brook Luers , Min Qian , Inbal Nahum-Shani , Connie Kasari , Daniel Almirall

A dynamic treatment regime is a sequence of decision rules in which each decision rule recommends treatment based on features of patient medical history such as past treatments and outcomes. Existing methods for estimating optimal dynamic…

统计方法学 · 统计学 2015-05-22 Kristin A. Linn , Eric B. Laber , Leonard A. Stefanski

Estimating optimal dynamic treatment regimes (DTRs) using observational data is often challenged by nonignorable missing covariates arsing from informative monitoring of patients in clinical practice. To address nonignorable missingness of…

统计方法学 · 统计学 2025-07-01 Jian Sun , Bo Fu , Li Su

In precision medicine, Dynamic Treatment Regimes (DTRs) are treatment protocols that adapt over time in response to a patient's observed characteristics. A DTR is a set of decision functions that takes an individual patient's information as…

统计方法学 · 统计学 2022-03-17 Cong Jiang , Michael Wallace , Mary Thompson

In recent years, large amounts of electronic health records (EHRs) concerning chronic diseases have been collected to facilitate medical diagnosis. Modeling the dynamic properties of EHRs related to chronic diseases can be efficiently done…

机器学习 · 计算机科学 2025-02-18 Di Wang , Yao Wang , Shao-Bo Lin

Dynamic treatment regimens (DTRs) are sequential decision rules tailored at each stage by potentially time-varying patient features and intermediate outcomes observed in previous stages. The complexity, patient heterogeneity and chronicity…

统计方法学 · 统计学 2016-11-09 Ying Liu , Yuanjia Wang , Michael R. Kosorok , Yingqi Zhao , Donglin Zeng

An optimal dynamic treatment regime (DTR) is a sequence of decision rules aimed at providing the best course of treatments individualized to patients. While conventional DTR estimation uses longitudinal data, such data can also be…

统计方法学 · 统计学 2025-02-06 Larry Dong , Eleanor Pullenayegum , Rodolphe Thiébaut , Olli Saarela

To achieve the goal of providing the best possible care to each patient, physicians need to customize treatments for patients with the same diagnosis, especially when treating diseases that can progress further and require additional…

统计方法学 · 统计学 2022-10-25 Xiao Li , Brent R Logan , S M Ferdous Hossain , Erica E M Moodie

Dynamic treatment regimes (DTRs) are critical to precision medicine, optimizing long-term outcomes through personalized, real-time decision-making in evolving clinical contexts, but require careful supervision for unsafe treatment risks.…

机器学习 · 计算机科学 2025-06-10 Yishan Shen , Yuyang Ye , Hui Xiong , Yong Chen

Dynamic treatment regimes (DTRs) consist of a sequence of decision rules, one per stage of intervention, that finds effective treatments for individual patients according to patient information history. DTRs can be estimated from models…

统计方法学 · 统计学 2021-12-07 Zeyu Bian , Erica EM Moodie , Susan M Shortreed , Sahir Bhatnagar

Public policies and medical interventions often involve dynamic treatment assignments, in which individuals receive a sequence of interventions over multiple stages. We study the statistical learning of optimal dynamic treatment regimes…

统计方法学 · 统计学 2025-05-21 Shosei Sakaguchi

Clinicians and researchers alike are increasingly interested in how best to personalize interventions. A dynamic treatment regimen (DTR) is a sequence of pre-specified decision rules which can be used to guide the delivery of a sequence of…

Dynamic treatment regimes (DTRs) are personalized, adaptive, multi-stage treatment plans that adapt treatment decisions both to an individual's initial features and to intermediate outcomes and features at each subsequent stage, which are…

机器学习 · 统计学 2022-09-22 Yichun Hu , Nathan Kallus
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