1 citations · 1 across the 3 of their papers we have counts for
6 papers
Integrative learning of individualized treatment rules from multiple studies with partially overlapping treatments
Yuan Bian, Donglin Zeng, Hyun-Joon Yang +2
An individualized treatment rule (ITR) tailors treatments to a patient's specific characteristics. However, randomized controlled trials (RCTs) are often underpowered to detect the…
Shared hidden-factor information framework for multiple behavioral tasks
Yuan Bian, Yuanjia Wang, Xingche Guo
Understanding cognitive processes in major depressive disorder (MDD) often relies on behavioral tasks, which are typically analyzed separately, overlooking potential correlations a…
Boosting methods for interval-censored data with regression and classification
Yuan Bian, Grace Y. Yi, Wenqing He
Boosting has garnered significant interest across both machine learning and statistical communities. Traditional boosting algorithms, designed for fully observed random samples, of…
Sample size and power determination for assessing overall SNP effects in joint modeling of longitudinal and time-to-event data
Yuan Bian, Shelley B. Bull
Longitudinal biomarkers are frequently collected in clinical studies due to their strong association with time-to-event outcomes. While considerable progress has been made in metho…
Boosting prediction with data missing not at random
Yuan Bian, Grace Y. Yi, Wenqing He
Boosting has emerged as a useful machine learning technique over the past three decades, attracting increased attention. Most advancements in this area, however, have primarily foc…
Joint modeling for learning decision-making dynamics in behavioral experiments
Yuan Bian, Xingche Guo, Yuanjia Wang
Major depressive disorder (MDD), a leading cause of disability and mortality, is associated with reward-processing abnormalities and concentration issues. Motivated by the probabil…