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In a tie-breaker design (TBD), subjects with high values of a running variable are given some (usually desirable) treatment, subjects with low values are not, and subjects in the middle are randomized. TBDs are intermediate between…

Methodology · Statistics 2025-05-12 Tim P. Morrison , Art B. Owen

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

Modeling disease progression through multiple stages is critical for clinical decision-making for chronic diseases, e.g., cancer, diabetes, chronic kidney diseases, and so on. Existing approaches often model the disease progression as a…

Machine Learning · Computer Science 2025-03-04 Haoyu Yang , Sanjoy Dey , Pablo Meyer

Objective: Our study objective is to design a feasible technology solution for health organizations to remove barriers to evidence-based clinical information retrieval, and improve Evidence-Based Practice. Methods: Literature from 2010 to…

Information Retrieval · Computer Science 2021-11-11 Alvet Miranda , Shah Jahan Miah

Despite their cost, randomized controlled trials (RCTs) are widely regarded as gold-standard evidence in disciplines ranging from social science to medicine. In recent decades, researchers have increasingly sought to reduce the resource…

Methodology · Statistics 2026-02-24 Guilherme Duarte

It is crucial to provide compatible treatment schemes for a disease according to various symptoms at different stages. However, most classification methods might be ineffective in accurately classifying a disease that holds the…

Machine Learning · Computer Science 2019-11-26 Jianguo Chen , Kenli Li , Huigui Rong , Kashif Bilal , Nan Yang , Keqin Li

Dynamic treatment regimens (DTRs), also known as treatment algorithms or adaptive interventions, play an increasingly important role in many health domains. DTRs are motivated to address the unique and changing needs of individuals by…

The US FDA's Project Optimus initiative that emphasizes dose optimization prior to marketing approval represents a pivotal shift in oncology drug development. It has a ripple effect for rethinking what changes may be made to conventional…

Methodology · Statistics 2024-06-04 Yuhan Li , Yiding Zhang , Gu Mi , Ji Lin

In clinical trials, response-adaptive randomization (RAR) has the appealing ability to assign more subjects to better-performing treatments based on interim results. The traditional RAR strategy alters the randomization ratio on a…

Methodology · Statistics 2021-10-01 David Merrell , Thevaa Chandereng , Yeonhee Park

A treatment regime formalizes personalized medicine as a function from individual patient characteristics to a recommended treatment. A high-quality treatment regime can improve patient outcomes while reducing cost, resource consumption,…

Methodology · Statistics 2015-04-30 Yichi Zhang , Eric B. Laber , Anastasios Tsiatis , Marie Davidian

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

This paper proposes a Workflow for Assessing Treatment effeCt Heterogeneity (WATCH) in clinical drug development targeted at clinical trial sponsors. WATCH is designed to address the challenges of investigating treatment effect…

Clinical trials with time-to-event endpoints, such as overall survival (OS) or progression-free survival (PFS), are fundamental for evaluating new treatments, particularly in immuno-oncology. However, modern therapies, such as…

Methodology · Statistics 2025-09-10 James Salsbury , Jeremy Oakley , Steven Julious , Lisa Hampson

Repetitive Scenario Design (RSD) is a randomized approach to robust design based on iterating two phases: a standard scenario design phase that uses $N$ scenarios (design samples), followed by randomized feasibility phase that uses $N_o$…

Systems and Control · Computer Science 2016-02-12 Giuseppe C. Calafiore

Decision theory recognizes two principal approaches to solving problems under uncertainty: probabilistic models and cognitive heuristics. However, engineers, public planners and decision-makers in other fields seem to employ solution…

Risk Management · Quantitative Finance 2025-03-14 Alexander Gutfraind

Triple difference designs have become increasingly popular in empirical economics. The advantage of a triple difference design is that, within a treatment group, it allows for another subgroup of the population -- potentially less impacted…

Econometrics · Economics 2025-06-04 Laura Caron

Clinicians prescribe antibiotics by looking at the patient's health record with an experienced eye. However, the therapy might be rendered futile if the patient has drug resistance. Determining drug resistance requires time-consuming…

Artificial Intelligence · Computer Science 2023-03-09 Honglin Shu , Pei Gao , Lingwei Zhu , Zheng Chen

With the uptake of targeted therapies, instead of the "one-fits-all" approach, modern randomized clinical trials (RCTs) often aim to develop treatments that target a subgroup of patients. Motivated by analyzing the Age-Related Eye Disease…

Applications · Statistics 2020-03-25 Yue Wei , Jason C. Hsu , Wei Chen , Emily Y. Chew , Ying Ding

We develop a marginal treatment effect based method to learn about causal effects in multiple treatment models with discrete instruments. We allow selection into treatment to be governed by a general class of threshold crossing models that…

Econometrics · Economics 2026-01-21 Vishal Kamat , Samuel Norris , Matthew Pecenco

Chronic kidney disease (CKD) represents a slowly progressive disorder that can eventually require renal replacement therapy (RRT) including dialysis or renal transplantation. Early identification of patients who will require RRT (as much as…

Machine Learning · Computer Science 2022-09-07 Daniel Lopez-Martinez , Christina Chen , Ming-Jun Chen