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The complexity of human cancer often results in significant heterogeneity in response to treatment. Precision medicine offers potential to improve patient outcomes by leveraging this heterogeneity. Individualized treatment rules (ITRs)…

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…

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

Causal machine learning (ML) methods hold great promise for advancing precision medicine by estimating personalized treatment effects. However, their reliability remains largely unvalidated in empirical settings. In this study, we assessed…

Machine Learning · Computer Science 2025-01-10 Hongruyu Chen , Helena Aebersold , Milo Alan Puhan , Miquel Serra-Burriel

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

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

Randomized trials typically estimate average relative treatment effects, but decisions on the benefit of a treatment are possibly better informed by more individualized predictions of the absolute treatment effect. In case of a binary…

Methodology · Statistics 2021-08-20 J Hoogland , J IntHout , M Belias , MM Rovers , RD Riley , FE Harrell , KGM Moons , TPA Debray , JB Reitsma

In many medical and business applications, researchers are interested in estimating individualized treatment effects using data from a randomized experiment. For example in medical applications, doctors learn the treatment effects from…

Methodology · Statistics 2022-03-01 Kevin Wu Han , Han Wu

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

Individualized treatment decisions can improve health outcomes, but using data to make these decisions in a reliable, precise, and generalizable way is challenging with a single dataset. Leveraging multiple randomized controlled trials…

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

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

Practitioners in medicine, business, political science, and other fields are increasingly aware that decisions should be personalized to each patient, customer, or voter. A given treatment (e.g. a drug or advertisement) should be…

Machine Learning · Statistics 2018-06-15 Alejandro Schuler , Michael Baiocchi , Robert Tibshirani , Nigam Shah

Individualized treatment rules (ITRs) aim to optimize healthcare by tailoring treatment decisions to patient-specific characteristics. Existing methods typically rely on either interpretable but inflexible models or highly flexible…

Methodology · Statistics 2026-02-13 Yasin Khadem Charvadeh , Katherine S. Panageas , Yuan Chen

In many practical tasks it is needed to estimate an effect of treatment on individual level. For example, in medicine it is essential to determine the patients that would benefit from a certain medicament. In marketing, knowing the persons…

Methodology · Statistics 2019-02-28 Aleksey Buzmakov

The burden of diseases is rising worldwide, with unequal treatment efficacy for patient populations that are underrepresented in clinical trials. Healthcare, however, is driven by the average population effect of medical treatments and,…

Machine Learning · Computer Science 2024-02-08 Ghadeer O. Ghosheh , Moritz Gögl , Tingting Zhu

In recent years, there has been a growing interest in the prediction of individualized treatment effects. While there is a rapidly growing literature on the development of such models, there is little literature on the evaluation of their…

Methodology · Statistics 2023-12-22 J Hoogland , O Efthimiou , TL Nguyen , TPA Debray

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

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

Clinical trials usually target average treatment effects, but treatment decisions are made for individuals. This tension motivates a common criticism of evidence-based medicine: a treatment that is beneficial on average may be inappropriate…

Applications · Statistics 2026-05-29 Zach Shahn , Mats Stensrud