English
Related papers

Related papers: Multicategory Angle-based Learning for Estimating …

200 papers

A main research goal in various studies is to use an observational data set and provide a new set of counterfactual guidelines that can yield causal improvements. Dynamic Treatment Regimes (DTRs) are widely studied to formalize this…

Machine Learning · Computer Science 2023-06-06 Soroush Saghafian

The International Classification of Diseases (ICD) serves as a definitive medical classification system encompassing a wide range of diseases and conditions. The primary objective of ICD indexing is to allocate a subset of ICD codes to a…

Computation and Language · Computer Science 2024-05-30 Xindi Wang , Robert E. Mercer , Frank Rudzicz

High-dose-rate (HDR) brachytherapy plays a critical role in the treatment of locally advanced cervical cancer but remains highly dependent on manual treatment planning expertise. The objective of this study is to develop a fully automated…

A dynamic treatment regime is a sequence of treatment decision rules tailored to an individual's evolving status over time. In precision medicine, much focus has been placed on finding an optimal dynamic treatment regime which, if followed…

Other Statistics · Statistics 2025-10-13 Chunyu Wang , Brian DM Tom

Dynamic treatment regimes (DTRs) are sequences of decision rules that recommend treatments based on patients' time-varying clinical conditions. The sequential multiple assignment randomized trial (SMART) is an experimental design that can…

Methodology · Statistics 2024-05-14 Xinru Wang , Nina Deliu , Yusuke Narita , Bibhas Chakraborty

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

Dynamic treatment regimes (DTRs) are personalized, adaptive strategies designed to guide the sequential allocation of treatments based on individual characteristics over time. Before each treatment assignment, covariate information is…

Methodology · Statistics 2025-07-24 Kai Chen , Yuqian Zhang

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 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

In both the fields of computer science and medicine there is very strong interest in developing personalized treatment policies for patients who have variable responses to treatments. In particular, I aim to find an optimal personalized…

Machine Learning · Computer Science 2014-07-01 Yousuf M. Soliman

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

Many policies involve dynamics in their treatment assignments, where individuals receive sequential interventions over multiple stages. We study estimation of an optimal dynamic treatment regime that guides the optimal treatment assignment…

Econometrics · Economics 2024-09-04 Shosei Sakaguchi

The sequential treatment decisions made by physicians to treat chronic diseases are formalized in the statistical literature as dynamic treatment regimes. To date, methods for dynamic treatment regimes have been developed under the…

Methodology · Statistics 2022-02-22 Janie Coulombe , Erica E. M. Moodie , Susan M. Shortreed , Christel Renoux

Inspired by advances in LLMs, reasoning-enhanced sequential recommendation performs multi-step deliberation before making final predictions, unlocking greater potential for capturing user preferences. However, current methods are…

Information Retrieval · Computer Science 2025-12-17 Yifan Shao , Peilin Zhou , Shoujin Wang , Weizhi Zhang , Xu Cai , Sunghun Kim

Establishing causality is a fundamental goal in fields like medicine and social sciences. While randomized controlled trials are the gold standard for causal inference, they are not always feasible or ethical. Observational studies can…

Statistics Theory · Mathematics 2024-12-03 Andrew Ying

We study a class of structured optimal control problems in which the main diagonal of the dynamic matrix is a linear function of the design variable. While such problems are in general challenging and nonconvex, for positive systems we…

Optimization and Control · Mathematics 2019-07-09 Neil K. Dhingra , Marcello Colombino , Mihailo R. Jovanović

A dynamic treatment regime is a sequence of medical decisions that adapts to the evolving clinical status of a patient over time. To facilitate personalized care, it is crucial to assess the probability of each available treatment option…

Methodology · Statistics 2024-11-05 Jiefeng Bi , Matteo Borrotti , Bernardo Nipoti

Evidence supporting the current World Health Organization recommendations of early antiretroviral therapy (ART) initiation for adolescents is inconclusive. We leverage a large observational data and compare, in terms of mortality and CD4…

Applications · Statistics 2019-04-04 Liangyuan Hu , Joseph W. Hogan

With the advancement in drug development, multiple treatments are available for a single disease. Patients can often benefit from taking multiple treatments simultaneously. For example, patients in Clinical Practice Research Datalink (CPRD)…

Applications · Statistics 2018-04-17 Muxuan Liang , Ye Ting , Haoda Fu

We develop methodology for a multistage decision problem with flexible number of stages in which the rewards are survival times that are subject to censoring. We present a novel Q-learning algorithm that is adjusted for censored data and…

Statistics Theory · Mathematics 2012-05-31 Yair Goldberg , Michael R. Kosorok