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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

In many important applications of precision medicine, the outcome of interest is time to an event (e.g., death, relapse of disease) and the primary goal is to identify the optimal individualized decision rule (IDR) to prolong survival time.…

Methodology · Statistics 2022-04-11 Yu Zhou , Lan Wang , Rui Song , Tuoyi Zhao

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

Medical treatments tailored to a patient's baseline characteristics hold the potential of improving patient outcomes while reducing negative side effects. Learning individualized treatment rules (ITRs) often requires aggregation of multiple…

Machine Learning · Statistics 2022-12-15 Jay Jojo Cheng , Jared D. Huling , Guanhua Chen

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

An individualized decision rule (IDR) is a decision function that assigns each individual a given treatment based on his/her observed characteristics. Most of the existing works in the literature consider settings with binary or finitely…

Methodology · Statistics 2023-01-31 Hengrui Cai , Chengchun Shi , Rui Song , Wenbin Lu

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 rules (ITRs) for treatment recommendation is an important topic for precision medicine as not all beneficial treatments work well for all individuals. Interpretability is a desirable property of ITRs, as it helps…

Methodology · Statistics 2023-11-06 Jacob M. Maronge , Jared D. Huling , Guanhua Chen

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

An optimal individualized treatment rule (ITR) is a function that takes a patient's characteristics, such as demographics, biomarkers, and treatment history, and outputs a treatment that is expected to give the best outcome for that…

Methodology · Statistics 2026-02-05 Augustine Wigle , Erica E. M. Moodie

The individualized treatment rule (ITR), which recommends an optimal treatment based on individual characteristics, has drawn considerable interest from many areas such as precision medicine, personalized education, and personalized…

Methodology · Statistics 2023-09-28 Qi Xu , Haoda Fu , Annie Qu

One primary goal of precision medicine is to estimate the individualized treatment rules (ITRs) that optimize patients' health outcomes based on individual characteristics. Health studies with multiple treatments are commonly seen in…

Methodology · Statistics 2025-05-07 Xuqiao Li , Qiuyan Zhou , Ying Wu , Ying Yan

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

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

Individualized treatment rule (ITR) recommends treatment on the basis of individual patient characteristics and the previous history of applied treatments and their outcomes. Despite the fact there are many ways to estimate ITR with binary…

Methodology · Statistics 2017-08-15 Pavel Shvechikov , Evgeniy Riabenko

In recent years, the field of precision medicine has seen many advancements. Significant focus has been placed on creating algorithms to estimate individualized treatment rules (ITR), which map from patient covariates to the space of…

Methodology · Statistics 2021-12-09 Kushal S. Shah , Haoda Fu , Michael R. Kosorok

The optimal dynamic treatment rule (ODTR) framework offers an approach for understanding which kinds of patients respond best to specific treatments -- in other words, treatment effect heterogeneity. Recently, there has been a proliferation…

Personalized decision-making, tailored to individual characteristics, is gaining significant attention. The optimal treatment regime aims to provide the best-expected outcome in the entire population, known as the value function. One…

Methodology · Statistics 2024-05-28 Yuwen Cheng , Shu Yang

This study investigates the problem of individualizing treatment allocations using stated preferences for treatments. If individuals know in advance how the assignment will be individualized based on their stated preferences, they may state…

Econometrics · Economics 2023-11-16 Daido Kido

Individualized treatment rules/recommendations (ITRs) aim to improve patient outcomes by tailoring treatments to the characteristics of each individual. However, when there are many treatment groups, existing methods face significant…

Methodology · Statistics 2025-05-27 Ke Zhu , Jianing Chu , Ilya Lipkovich , Wenyu Ye , Shu Yang