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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

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

An individualized treatment regime (ITR) is a decision rule that assigns treatments based on patients' characteristics. The value function of an ITR is the expected outcome in a counterfactual world had this ITR been implemented. Recently,…

Methodology · Statistics 2023-01-16 Pan Zhao , Julie Josse , Shu Yang

An individualized treatment rule (ITR) tailors treatments to a patient's specific characteristics. However, randomized controlled trials (RCTs) are often underpowered to detect the treatment effect heterogeneity needed for reliable ITR…

Methodology · Statistics 2026-04-14 Yuan Bian , Donglin Zeng , Hyun-Joon Yang , Leanne M. Williams , Yuanjia Wang

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

We develop a prediction-based prescriptive model for learning optimal personalized treatments for patients based on their Electronic Health Records (EHRs). Our approach consists of: (i) predicting future outcomes under each possible therapy…

Machine Learning · Statistics 2018-12-06 Ruidi Chen , Ioannis Paschalidis

Although there is now a large literature on policy evaluation and learning, much of the prior work assumes that the treatment assignment of one unit does not affect the outcome of another unit. Unfortunately, ignoring interference can lead…

Methodology · Statistics 2025-04-02 Yi Zhang , Kosuke Imai

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

Recent development in the data-driven decision science has seen great advances in individualized decision making. Given data with individual covariates, treatment assignments and outcomes, policy makers best individualized treatment rule…

Machine Learning · Statistics 2020-06-29 Weibin Mo , Zhengling Qi , Yufeng Liu

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

Modern precision medicine aims to utilize real-world data to provide the best treatment for an individual patient. An individualized treatment rule (ITR) maps each patient's characteristics to a recommended treatment scheme that maximizes…

Applications · Statistics 2025-01-07 Andong Wang , Kelly Wentzlof , Johnny Rajala , Miontranese Green , Yunshu Zhang , Shu Yang

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

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

Estimating heterogeneous treatment effects (HTEs) is crucial for precision medicine. While multiple studies can improve the generalizability of results, leveraging them for estimation is statistically challenging. Existing approaches often…

Methodology · Statistics 2025-12-22 Cathy Shyr , Boyu Ren , Prasad Patil , Giovanni Parmigiani

Learning heterogeneous treatment effects (HTEs) is an important problem across many fields. Most existing methods consider the setting with a single treatment arm and a single outcome metric. However, in many real world domains, experiments…

Machine Learning · Computer Science 2022-06-13 Leon Yao , Caroline Lo , Israel Nir , Sarah Tan , Ariel Evnine , Adam Lerer , Alex Peysakhovich

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

Machine learning can help personalized decision support by learning models to predict individual treatment effects (ITE). This work studies the reliability of prediction-based decision-making in a task of deciding which action $a$ to take…

Machine Learning · Statistics 2019-06-07 Iiris Sundin , Peter Schulam , Eero Siivola , Aki Vehtari , Suchi Saria , Samuel Kaski

Estimating individualized treatment rules (ITRs) is fundamental to precision medicine, where the goal is to tailor treatment decisions to individual patient characteristics. While numerous methods have been developed for ITR estimation,…

Methodology · Statistics 2026-05-15 Eun Jeong Oh , Min Qian

Individualized treatment regimes (ITRs) aim to improve clinical outcomes by assigning treatment based on patient-specific characteristics. However, existing methods often struggle with high-dimensional covariates, limiting accuracy,…

Machine Learning · Statistics 2026-01-13 Sungtaek Son , Eardi Lila , Kwun Chuen Gary Chan

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
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