10 citations · 34 across the 21 of their papers we have counts for
21 papers
Neural Networks as Linear Regression: An Introduction for Statisticians
Abigail Loe, Susan Murray, Zhenke Wu
Neural networks are a commonly used prediction tool in computer science and statistics. However, the barrier to entry of this interesting field remains high, particularly for class…
Bayesian Active Questionnaire Design for Cause-of-Death Assignment Using Verbal Autopsies
Toshiya Yoshida, Trinity Shuxian Fan, Tyler McCormick +2
Only about one-third of the deaths worldwide are assigned a medically-certified cause, and understanding the causes of deaths occurring outside of medical facilities is logisticall…
Dynamic Survival Transformers for Causal Inference with Electronic Health Records
Prayag Chatha, Yixin Wang, Zhenke Wu +1
In medicine, researchers often seek to infer the effects of a given treatment on patients' outcomes. However, the standard methods for causal survival analysis make simplistic assu…
Outcome Adaptive Propensity Score Methods for Handling Censoring and High-Dimensionality: Application to Insurance Claims
Youfei Yu, Jiacong Du, Min Zhang +3
Propensity scores are commonly used to reduce the confounding bias in non-randomized observational studies for estimating the average treatment effect. An important assumption unde…
Variance as a predictor of health outcomes: Subject-level trajectories and variability of sex hormones to predict body fat changes in peri- and post-menopausal women
Irena Chen, Zhenke Wu, Siobán D. Harlow +3
Longitudinal biomarker data and cross-sectional outcomes are routinely collected in modern epidemiology studies, often with the goal of informing tailored early intervention decisi…
baker: An R package for Nested Partially-Latent Class Models
Irena B Chen, Qiyuan Shi, Scott L Zeger +1
This paper describes and illustrates the functionality of the baker R package. The package estimates a suite of nested partially-latent class models (NPLCM) for multivariate binary…
Probabilistic Learning of Treatment Trees in Cancer
Tsung-Hung Yao, Zhenke Wu, Karthik Bharath +2
Accurate identification of synergistic treatment combinations and their underlying biological mechanisms is critical across many disease domains, especially cancer. In translationa…
Tree-informed Bayesian multi-source domain adaptation: cross-population probabilistic cause-of-death assignment using verbal autopsy
Zhenke Wu, Zehang Richard Li, Irena Chen +1
Determining causes of deaths (COD) occurred outside of civil registration and vital statistics systems is challenging. A technique called verbal autopsy (VA) is widely adopted to g…
Bayesian Nested Latent Class Models for Cause-of-Death Assignment using Verbal Autopsies Across Multiple Domains
Zehang Richard Li, Zhenke Wu, Irena Chen +1
Understanding cause-specific mortality rates is crucial for monitoring population health and designing public health interventions. Worldwide, two-thirds of deaths do not have a ca…
Kernel Deformed Exponential Families for Sparse Continuous Attention
Alexander Moreno, Supriya Nagesh, Zhenke Wu +2
Attention mechanisms take an expectation of a data representation with respect to probability weights. This creates summary statistics that focus on important features. Recently, (…
Dynamic statistical inference in massive datastreams
Jingshen Wang, Lilun Du, Changliang Zou +1
Modern technological advances have expanded the scope of applications requiring analysis of large-scale datastreams that comprise multiple indefinitely long time series. There is a…
Assessing Time-Varying Causal Effect Moderation in the Presence of Cluster-Level Treatment Effect Heterogeneity
Jieru Shi, Zhenke Wu, Walter Dempsey
The micro-randomized trial (MRT) is a sequential randomized experimental design to empirically evaluate the effectiveness of mobile health (mHealth) intervention components that ma…
A Hierarchical Integrative Group LASSO (HiGLASSO) Framework for Analyzing Environmental Mixtures
Jonathan Boss, Alexander Rix, Yin-Hsiu Chen +6
Environmental health studies are increasingly measuring multiple pollutants to characterize the joint health effects attributable to exposure mixtures. However, the underlying dose…
A Robust Functional EM Algorithm for Incomplete Panel Count Data
Alexander Moreno, Zhenke Wu, Jamie Yap +5
Panel count data describes aggregated counts of recurrent events observed at discrete time points. To understand dynamics of health behaviors, the field of quantitative behavioral…
Weakly-supervised Multi-output Regression via Correlated Gaussian Processes
Seokhyun Chung, Raed Al Kontar, Zhenke Wu
Multi-output regression seeks to borrow strength and leverage commonalities across different but related outputs in order to enhance learning and prediction accuracy. A fundamental…
Regression Analysis of Dependent Binary Data for Estimating Disease Etiology from Case-Control Studies
Zhenke Wu, Irena Chen
In large-scale disease etiology studies, epidemiologists often need to use multiple binary measures of unobserved causes of disease that are not perfectly sensitive or specific to…
A Bayesian Approach to Restricted Latent Class Models for Scientifically-Structured Clustering of Multivariate Binary Outcomes
Zhenke Wu, Livia Casciola-Rosen, Antony Rosen +1
In this paper, we propose a general framework for combining evidence of varying quality to estimate underlying binary latent variables in the presence of restrictions imposed to re…
Estimating AutoAntibody Signatures to Detect Autoimmune Disease Patient Subsets
Zhenke Wu, Livia Casciola-Rosen, Ami A. Shah +2
Autoimmune diseases are characterized by highly specific immune responses against molecules in self-tissues. Different autoimmune diseases are characterized by distinct immune resp…
Nested Partially-Latent Class Models for Dependent Binary Data; Estimating Disease Etiology
Zhenke Wu, Maria Deloria-Knoll, Scott Zeger
The Pneumonia Etiology Research for Child Health (PERCH) study seeks to use modern measurement technology to infer the causes of pneumonia for which gold-standard evidence is unava…
Estimation of Treatment Effects in Matched-Pair Cluster Randomized Trials by Calibrating Covariate Imbalance between Clusters
Zhenke Wu, Constantine E. Frangakis, Thomas A. Louis +1
We address estimation of intervention effects in experimental designs in which (a) interventions are assigned at the cluster level; (b) clusters are selected to form pairs, matched…
Partially-Latent Class Models (pLCM) for Case-Control Studies of Childhood Pneumonia Etiology
Zhenke Wu, Maria Deloria-Knoll, Laura L. Hammitt +1
In population studies on the etiology of disease, one goal is the estimation of the fraction of cases attributable to each of several causes. For example, pneumonia is a clinical d…