160 citations · 246 across the 13 of their papers we have counts for
13 papers
Incorporating Participants' Welfare into Sequential Multiple Assignment Randomized Trials
Xinru Wang, Nina Deliu, Yusuke Narita +1
Dynamic treatment regimes (DTRs) are sequences of decision rules that recommend treatments based on patients' time-varying clinical conditions. The sequential multiple assignment r…
Making SMART decisions in prophylaxis and treatment studies
Robert K. Mahar, Katherine J. Lee, Bibhas Chakraborty +2
The optimal prophylaxis, and treatment if the prophylaxis fails, for a disease may be best evaluated using a sequential multiple assignment randomised trial (SMART). A SMART is a m…
A Flexible Micro-Randomized Trial Design and Sample Size Considerations
Jing Xu, Xiaoxi Yan, Caroline Figueroa +2
Technological advancements have made it possible to deliver mobile health interventions to individuals. A novel framework that has emerged from such advancements is the just-in-tim…
Reinforcement Learning in Modern Biostatistics: Constructing Optimal Adaptive Interventions
Nina Deliu, Joseph Jay Williams, Bibhas Chakraborty
In recent years, reinforcement learning (RL) has acquired a prominent position in health-related sequential decision-making problems, gaining traction as a valuable tool for delive…
Deep learning for temporal data representation in electronic health records: A systematic review of challenges and methodologies
Feng Xie, Han Yuan, Yilin Ning +5
Objective: Temporal electronic health records (EHRs) can be a wealth of information for secondary uses, such as clinical events prediction or chronic disease management. However, c…
AutoScore-Imbalance: An interpretable machine learning tool for development of clinical scores with rare events data
Han Yuan, Feng Xie, Marcus Eng Hock Ong +7
Background: Medical decision-making impacts both individual and public health. Clinical scores are commonly used among a wide variety of decision-making models for determining the…
AutoScore-Survival: Developing interpretable machine learning-based time-to-event scores with right-censored survival data
Feng Xie, Yilin Ning, Han Yuan +4
Scoring systems are highly interpretable and widely used to evaluate time-to-event outcomes in healthcare research. However, existing time-to-event scores are predominantly created…
Multi-Level Micro-Randomized Trial: Detecting the Proximal Effect of Messages on Physical Activity
Jing Xu, Xiaoxi Yan, Caroline Figueroa +2
Technological advancements in mobile devices have made it possible to deliver mobile health interventions to individuals. A novel intervention framework that emerges from such adva…
Estimating the Optimal Linear Combination of Biomarkers using Spherically Constrained Optimization
Priyam Das, Debsurya De, Raju Maiti +5
In the context of a binary classification problem, the optimal linear combination of continuous predictors can be estimated by maximizing an empirical estimate of the area under th…
A distribution-free smoothed combination method of biomarkers to improve diagnostic accuracy in multi-category classification
Raju Maiti, Jialiang Li, Priyam Das +3
Results from multiple diagnostic tests are usually combined to improve the overall diagnostic accuracy. For binary classification, maximization of the empirical estimate of the are…
SMARTp: A SMART design for non-surgical treatments of chronic periodontitis with spatially-referenced and non-randomly missing skewed outcomes
Jing Xu, Dipankar Bandyopadhyay, Sedigheh Mirzaei +2
This paper proposes dynamic treatment regimes for choosing individualized effective treatment strategies of chronic periodontal disease. R codes for implementing the proposed sampl…
A Novel Approach To Assess Dynamic Treatment Regimes Embedded In A Smart With An Ordinal Outcome
Palash Ghosh, Xiaoxi Yan, Bibhas Chakraborty
Sequential multiple assignment randomized trials (SMARTs) are used to construct data-driven optimal intervention strategies for subjects based on their intervention and covariate h…
Non-Inferiority and Equivalence Tests in A Sequential Multiple-Assignment Randomized Trial (SMART)
Palash Ghosh, Inbal Nahum-Shani, Bonnie Spring +1
Adaptive interventions (AIs) are increasingly becoming popular in medical and behavioral sciences. An AI is a sequence of individualized intervention options that specify for whom…