27 citations · 68 across the 25 of their papers we have counts for
25 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…
Maximin Learning of Individualized Treatment Effect on Multi-Domain Outcomes
Yuying Lu, Wenbo Fei, Yuanjia Wang +1
Precision mental health requires treatment decisions that account for heterogeneous symptoms reflecting multiple clinical domains. However, existing methods for estimating individu…
Semiparametric Analysis of Interval-Censored Data Subject to Inaccurate Diagnoses with A Terminal Event
Yuhao Deng, Donglin Zeng, Yuanjia Wang
Interval-censoring frequently occurs in studies of chronic diseases where disease status is inferred from intermittently collected biomarkers. Although many methods have been devel…
Debiased Inference for High-Dimensional Regression Models Based on Profile M-Estimation
Yuhao Deng, Yi Wang, Yu Gu +2
Debiased inference for high-dimensional regression models has received substantial recent attention to ensure regularized estimators have valid inference. Many existing methods foc…
Multi-level Latent Variable Models for Coheritability Analysis in Electronic Health Records
Yinjun Zhao, Nicholas Tatonetti, Yuanjia Wang
Electronic health records (EHRs) linked with familial relationship data offer a unique opportunity to investigate the genetic architecture of complex phenotypes at scale. However,…
An Integrative Approach for Subtyping Mental Disorders Using Multimodal Data
Yinjun Zhao, Yuanjia Wang, Ying LIu
Understanding the biological and behavioral heterogeneity underlying psychiatric disorders is critical for advancing precision diagnosis, treatment, and prevention. This paper addr…
Cumulative Marginal Mean Model for Assessing Sequential Effects Using Digital Health Data
Xingche Guo, Zexi Cai, Yuanjia Wang +1
Mobile health (mHealth) leverages digital technologies, such as mobile phones, to capture objective, frequent, and real-world digital phenotypes from individuals, enabling the deli…
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…
Dynamic Classification of Latent Disease Progression with Auxiliary Surrogate Labels
Zexi Cai, Donglin Zeng, Karen S. Marder +2
Disease progression prediction based on patients' evolving health information is challenging when true disease states are unknown due to diagnostic capabilities or high costs. For…
Fusing Individualized Treatment Rules Using Secondary Outcomes
Daiqi Gao, Yuanjia Wang, Donglin Zeng
An individualized treatment rule (ITR) is a decision rule that recommends treatments for patients based on their individual feature variables. In many practices, the ideal ITR for…
HMM for Discovering Decision-Making Dynamics Using Reinforcement Learning Experiments
Xingche Guo, Donglin Zeng, Yuanjia Wang
Major depressive disorder (MDD) presents challenges in diagnosis and treatment due to its complex and heterogeneous nature. Emerging evidence indicates that reward processing abnor…
A Hierarchical Random Effects State-space Model for Modeling Brain Activities from Electroencephalogram Data
Xingche Guo, Bin Yang, Ji Meng Loh +2
Mental disorders present challenges in diagnosis and treatment due to their complex and heterogeneous nature. Electroencephalogram (EEG) has shown promise as a potential biomarker…
Learning Optimal Biomarker-Guided Treatment Policy for Chronic Disorders
Bin Yang, Xingche Guo, Ji Meng Loh +2
Electroencephalogram (EEG) provides noninvasive measures of brain activity and is found to be valuable for diagnosis of some chronic disorders. Specifically, pre-treatment EEG sign…
Mixed-Response State-Space Model for Analyzing Multi-Dimensional Digital Phenotypes
Tianchen Xu, Yuan Chen, Donglin Zeng +1
Digital technologies (e.g., mobile phones) can be used to obtain objective, frequent, and real-world digital phenotypes from individuals. However, modeling these data poses substan…
Learning Optimal Dynamic Treatment Regimens Subject to Stagewise Risk Controls
Mochuan Liu, Yuanjia Wang, Haoda Fu +1
Dynamic treatment regimens (DTRs) aim at tailoring individualized sequential treatment rules that maximize cumulative beneficial outcomes by accommodating patients' heterogeneity i…
Learning non-monotone optimal individualized treatment regimes
Trinetri Ghosh, Yanyuan Ma, Wensheng Zhu +1
We propose a new modeling and estimation approach to select the optimal treatment regime from different options through constructing a robust estimating equation. The method is pro…
Evaluating Effectiveness of Public Health Intervention Strategies for Mitigating COVID-19 Pandemic
Shanghong Xie, Wenbo Wang, Qinxia Wang +2
Coronavirus disease 2019 (COVID-19) pandemic is an unprecedented global public health challenge. In the United States (US), state governments have implemented various non-pharmaceu…
A General Framework of Nonparametric Feature Selection in High-Dimensional Data
Hang Yu, Yuanjia Wang, Donglin Zeng
Nonparametric feature selection in high-dimensional data is an important and challenging problem in statistics and machine learning fields. Most of the existing methods for feature…
Representation Learning for Integrating Multi-domain Outcomes to Optimize Individualized Treatments
Yuan Chen, Donglin Zeng, Tianchen Xu +1
For mental disorders, patients' underlying mental states are non-observed latent constructs which have to be inferred from observed multi-domain measurements such as diagnostic sym…
Estimation of Genetic Risk Function with Covariates in the Presence of Missing Genotypes
Annie J. Lee, Karen Marder, Helen Mejia-Santana +4
In genetic epidemiological studies, family history data are collected on relatives of study participants and used to estimate the age-specific risk of disease for individuals who c…
Robust Hybrid Learning for Estimating Personalized Dynamic Treatment Regimens
Ying Liu, Yuanjia Wang, Michael R. Kosorok +2
Dynamic treatment regimens (DTRs) are sequential decision rules tailored at each stage by potentially time-varying patient features and intermediate outcomes observed in previous s…
Fused kernel-spline smoothing for repeatedly measured outcomes in a generalized partially linear model with functional single index
Fei Jiang, Yanyuan Ma, Yuanjia Wang
We propose a generalized partially linear functional single index risk score model for repeatedly measured outcomes where the index itself is a function of time. We fuse the nonpar…
Combining isotonic regression and EM algorithm to predict genetic risk under monotonicity constraint
Jing Qin, Tanya P. Garcia, Yanyuan Ma +3
In certain genetic studies, clinicians and genetic counselors are interested in estimating the cumulative risk of a disease for individuals with and without a rare deleterious muta…