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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

With the emergence of precision medicine, estimating optimal individualized decision rules (IDRs) has attracted tremendous attention in many scientific areas. Most existing literature has focused on finding optimal IDRs that can maximize…

Methodology · Statistics 2022-06-28 Zhengling Qi , Jong-Shi Pang , Yufeng Liu

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

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

Personalized medicine has gained much popularity recently as a way of providing better healthcare by tailoring treatments to suit individuals. Our research, motivated by the UK INTERVAL blood donation trial, focuses on estimating the…

Methodology · Statistics 2023-02-24 Yuejia Xu , Angela M. Wood , David J. Roberts , Brian D. M. Tom

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) 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

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

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

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

Recent exploration of optimal individualized decision rules (IDRs) for patients in precision medicine has attracted a lot of attention due to the heterogeneous responses of patients to different treatments. In the existing literature of…

Optimization and Control · Mathematics 2019-08-29 Zhengling Qi , Ying Cui , Yufeng Liu , Jong-Shi Pang

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

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

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 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

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

Personalized medicine has received increasing attention among statisticians, computer scientists, and clinical practitioners. A major component of personalized medicine is the estimation of individualized treatment rules (ITRs). Recently,…

Methodology · Statistics 2015-08-14 Xin Zhou , Nicole Mayer-Hamblett , Umer Khan , Michael R. Kosorok

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

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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