42 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of Colorado AnschutzUS8 papers
- Harvard UniversityUS2 papers
- Heidelberg UniversityDE2 papers
- Johns Hopkins UniversityUS2 papers
- University Hospital HeidelbergDE2 papers
- University of Colorado DenverUS2 papers
- University of FloridaUS2 papers
- University of North Carolina at Chapel HillUS2 papers
- Center for Global HealthUS1 paper
- Cleveland ClinicUS1 paper
- Johnson UniversityUS1 paper
- Konkuk UniversityKR1 paper
16 papers
BioNeuralNet: A Graph Neural Network based Multi-Omics Network Data Analysis Tool
Vicente Ramos, Sundous Hussein, Mohamed Abdel-Hafiz +6
Multi-omics data offer unprecedented insights into complex biological systems, yet their high dimensionality, sparsity, and intricate interactions pose significant analytical chall…
Excess risk of heat-related hospitalization associated with temperature and PM2.5 among older adults
Lauren Mock, Rachel C. Nethery, Poonam Gandhi +5
Background: With rising temperatures and an aging population, understanding how to prevent heat-related illness among older adults will be increasingly crucial. Despite biological…
Residual-based Alternative Partial Least Squares for Generalized Functional Linear Models
Yue Wang, Xiao Wang, Joseph G. Ibrahim +1
Many biomedical studies collect high-dimensional medical imaging data to identify biomarkers for the detection, diagnosis, and treatment of human diseases. Consequently, it is cruc…
GeoDEN: A Visual Exploration Tool for Analysing the Geographic Spread of Dengue Serotypes
Aidan Marler, Yannik Roell, Steffen Knoblauch +3
Static maps and animations remain popular in spatial epidemiology of dengue, limiting the analytical depth and scope of visualisations. Over half of the global population live in d…
Walking fingerprinting
Lily Koffman, Ciprian Crainiceanu, Andrew Leroux
We consider the problem of predicting an individual's identity from accelerometry data collected during walking. In a previous paper we introduced an approach that transforms the a…
Fast, effective, and coherent time series modeling using the sparsity-ranked lasso
Ryan Peterson, Joseph Cavanaugh
The sparsity-ranked lasso (SRL) has been developed for model selection and estimation in the presence of interactions and polynomials. The main tenet of the SRL is that an algorith…
Ranked Sparsity: A Cogent Regularization Framework for Selecting and Estimating Feature Interactions and Polynomials
Ryan A. Peterson, Joseph E. Cavanaugh
We explore and illustrate the concept of ranked sparsity, a phenomenon that often occurs naturally in modeling applications when an expected disparity exists in the quality of info…
Measurement Error in Meta-Analysis (MEMA) -- a Bayesian framework for continuous outcome data
Harlan Campbell, Valentijn M. T. de Jong, Lauren Maxwell +3
Ideally, a meta-analysis will summarize data from several unbiased studies. Here we consider the less than ideal situation in which contributing studies may be compromised by measu…
A Calibration Approach to Transportability and Data-Fusion with Observational Data
Kevin P. Josey, Fan Yang, Debashis Ghosh +1
Two important considerations in clinical research studies are proper evaluations of internal and external validity. While randomized clinical trials can overcome several threats to…
Transporting Experimental Results with Entropy Balancing
Kevin P. Josey, Seth A. Berkowitz, Debashis Ghosh +1
We show how entropy balancing can be used for transporting experimental treatment effects from a trial population onto a target population. This method is doubly-robust in the sens…
Analysis of regression discontinuity designs using censored data
Youngjoo Cho, Chen Hu, Debashis Ghosh
In medical settings, treatment assignment may be determined by a clinically important covariate that predicts patients' risk of event. There is a class of methods from the social s…
A Framework for Covariate Balance using Bregman Distances
Kevin P. Josey, Elizabeth Juarez-Colunga, Fan Yang +1
A common goal in observational research is to estimate marginal causal effects in the presence of confounding variables. One solution to this problem is to use the covariate distri…
Predictive Directions for Individualized Treatment Selection in Clinical Trials
Debashis Ghosh, Youngjoo Cho
In many clinical trials, individuals in different subgroups have experience differential treatment effects. This leads to individualized differences in treatment benefit. In this a…
Revisiting Graph Construction for Fast Image Segmentation
Zizhao Zhang, Fuyong Xing, Hanzi Wang +4
In this paper, we propose a simple but effective method for fast image segmentation. We re-examine the locality-preserving character of spectral clustering by constructing a graph…
Reducing decision errors in the paired comparison of the diagnostic accuracy of screening tests with Gaussian outcomes
Brandy M. Ringham, Todd A. Alonzo, John T. Brinton +4
Scientists often use a paired comparison of the areas under the receiver operating characteristic curves to decide which continuous cancer screening test has the best diagnostic ac…
A General formulation for standardization of rates as a method to control confounding by measured and unmeasured disease risk factors
Steven D. Mark
Standardization, a common approach for controlling confounding in population-studies or data from disease registries, is defined to be a weighted average of stratum specific rates.…