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An individualized treatment rule (ITR) is a decision rule that recommends treatments for patients based on their individual feature variables. In many practices, the ideal ITR for the primary outcome is also expected to cause minimal harm…

Methodology · Statistics 2024-05-24 Daiqi Gao , Yuanjia Wang , Donglin Zeng

An individualized treatment rule (ITR) is a decision rule that aims to improve individual patients health outcomes by recommending optimal treatments according to patients specific information. In observational studies, collected data may…

Methodology · Statistics 2023-10-03 Zeyu Bian , Erica EM Moodie , Susan M Shortreed , Sylvie D Lambert , Sahir Bhatnagar

To promote precision medicine, individualized treatment regimes (ITRs) are crucial for optimizing the expected clinical outcome based on patient-specific characteristics. However, existing ITR research has primarily focused on scenarios…

Methodology · Statistics 2024-02-20 Chang Wang , Lu Wang

Individualized treatment rules (ITR) can improve health outcomes by recognizing that patients may respond differently to treatment and assigning therapy with the most desirable predicted outcome for each individual. Flexible and efficient…

Methodology · Statistics 2017-09-25 Brent R. Logan , Rodney Sparapani , Robert E. McCulloch , Purushottam W. Laud

Estimating individualized treatment rules (ITRs) is crucial for tailoring interventions in precision medicine. Typical ITR estimation methods rely on conditional average treatment effects (CATEs) to guide treatment assignments. However,…

Methodology · Statistics 2025-10-20 Peng Wu , Qing Jiang , Shanshan Luo , Zhi Geng

Precision medicine is an emerging scientific topic for disease treatment and prevention that takes into account individual patient characteristics. It is an important direction for clinical research, and many statistical methods have been…

Methodology · Statistics 2017-02-17 Jingxiang Chen , Haoda Fu , Xuanyao He , Michael R. Kosorok , Yufeng Liu

We develop a mathematical framework to define an optimal individualized treatment rule (ITR) within the context of prioritized outcomes in a randomized controlled trial. Our optimality criterion is based on the framework of generalized…

Methodology · Statistics 2025-06-17 François Petit , Gérard Biau , Raphaël Porcher

Individualized treatment rules (ITRs) are considered a promising recipe to deliver better policy interventions. One key ingredient in optimal ITR estimation problems is to estimate the average treatment effect conditional on a subject's…

Methodology · Statistics 2021-03-16 Hongming Pu , Bo Zhang

In precision medicine, one of the most important problems is estimating the optimal individualized treatment rules (ITR), which typically involves recommending treatment decisions based on fully observed individual characteristics of…

Methodology · Statistics 2025-10-15 Yue Zhang , Shanshan Luo , Zhi Geng , Yangbo He

The field of precision medicine aims to tailor treatment based on patient-specific factors in a reproducible way. To this end, estimating an optimal individualized treatment regime (ITR) that recommends treatment decisions based on patient…

Individualized treatment recommendation (ITR) is an important analytic framework for precision medicine. The goal is to assign proper treatments to patients based on their individual characteristics. From the machine learning perspective,…

Machine Learning · Statistics 2020-04-07 Haomiao Meng , Ying-Qi Zhao , Haoda Fu , Xingye Qiao

Individualized treatment rules (ITRs) are deterministic decision rules that recommend treatments to individuals based on their characteristics. Though ubiquitous in medicine, ITRs are hardly ever evaluated in randomized controlled trials.…

Methodology · Statistics 2023-08-22 François Grolleau , Francois Petit , Raphaël Porcher

Randomized controlled trials typically analyze the effectiveness of treatments with the goal of making treatment recommendations for patient subgroups. With the advance of electronic health records, a great variety of data has been…

Machine Learning · Computer Science 2021-03-31 Zhiliang Wu , Yinchong Yang , Yunpu Ma , Yushan Liu , Rui Zhao , Michael Moor , Volker Tresp

Learning individualized treatment rules (ITRs) is an important topic in precision medicine. Current literature mainly focuses on deriving ITRs from a single source population. We consider the observational data setting when the source…

Machine Learning · Statistics 2023-07-04 Rui Chen , Jared D. Huling , Guanhua Chen , Menggang Yu

Identifying patients who benefit from a treatment is a key aspect of personalized medicine, which allows the development of individualized treatment rules (ITRs). Many machine learning methods have been proposed to create such rules.…

Individualized treatment rules, cornerstones of precision medicine, inform patient treatment decisions with the goal of optimizing patient outcomes. These rules are generally unknown functions of patients' pre-treatment covariates, meaning…

Methodology · Statistics 2025-04-23 Philippe Boileau , Ning Leng , Sandrine Dudoit

Individualized treatment effect lies at the heart of precision medicine. Interpretable individualized treatment rules (ITRs) are desirable for clinicians or policymakers due to their intuitive appeal and transparency. The gold-standard…

Methodology · Statistics 2021-08-20 Lili Wu , Shu Yang

Precision medicine involves developing individualized treatment regimes (ITRs) which allow for treatment decisions to be tailored to patient characteristics. Naturally, the identification of the optimal regime, that is, the rule which…

Methodology · Statistics 2025-09-30 Misha Dolmatov , Erica E. M. Moodie , David A. Stephens , Dipankar Bandyopadhyay

Individualized treatment rules (ITRs) tailor treatments according to individual patient characteristics. They can significantly improve patient care and are thus becoming increasingly popular. The data collected during randomized clinical…

Methodology · Statistics 2015-06-30 Stanislav Minsker , Ying-Qi Zhao , Guang Cheng

Data-driven individualized decision making has recently received increasing research interests. Most existing methods rely on the assumption of no unmeasured confounding, which unfortunately cannot be ensured in practice especially in…

Methodology · Statistics 2022-12-26 Zhengling Qi , Rui Miao , Xiaoke Zhang
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