6 citations · 11 across the 7 of their papers we have counts for
8 papers
Trustworthy AI/ML Regression and Unbiased Causal Inference for Real-World Data
Yifei Xu, Hwiyoung Lee, Zhenyao Ye +5
Real-World Data (RWD), with its large sample sizes and rich clinical detail, offers a compelling alternative to randomized controlled trials (RCTs) for studying treatment effects i…
Estimate Time-Varying Exposure Effects via Ensemble Learning-based Marginal Structural Model with Application to Adolescent Cognitive Development Study
Zhiwei Zhao, Chixiang Chen, Shuo Chen
Evaluating the effects of time-varying exposures is essential for longitudinal studies. The effect estimation becomes increasingly challenging when dealing with hundreds of time-de…
A New Integrative Learning Framework for Integrating Multiple Secondary Outcomes into Primary Outcome Analysis: A Case Study on Liver Health
Daxuan Deng, Peisong Han, Shuo Chen +2
In the era of big data, secondary outcomes have become increasingly important alongside primary outcomes. These secondary outcomes, which can be derived from traditional endpoints…
Modeling Interconnected Modules in Multivariate Outcomes: Evaluating the Impact of Alcohol Intake on Plasma Metabolomics
Yifan Yang, Chixiang Chen, Hwiyoung Lee +2
Alcohol consumption has been shown to influence cardiovascular mechanisms in humans, leading to observable alterations in the plasma metabolomic profile. Regression models are comm…
Multiple Imputation Method for High-Dimensional Neuroimaging Data
Tong Lu, Chixiang Chen, Hsin-Hsiung Huang +3
Missingness is a common issue for neuroimaging data, and neglecting it in downstream statistical analysis can introduce bias and lead to misguided inferential conclusions. It is th…
The Effect of Alcohol intake on Brain White Matter Microstructural Integrity: A New Causal Inference Framework for Incomplete Phenomic Data
Chixiang Chen, Shuo Chen, Zhenyao Ye +3
Although substance use, such as alcohol intake, is known to be associated with cognitive decline during aging, its direct influence on the central nervous system remains incomplete…
Integrative data analysis where partial covariates have complex non-linear effects by using summary information from an external data
Jia Liang, Shuo Chen, Peter Kochunov +2
A full parametric and linear specification may be insufficient to capture complicated patterns in studies exploring complex features, such as those investigating age-related change…
Covariance Matrix Estimation for High-Throughput Biomedical Data with Interconnected Communities
Yifan Yang, Chixiang Chen, Shuo Chen
Estimating a covariance matrix is central to high-dimensional data analysis. Empirical analyses of high-dimensional biomedical data, including genomics, proteomics, microbiome, and…