1 citations · 5 across the 7 of their papers we have counts for
7 papers
Efficient computation of high-dimensional penalized piecewise constant hazard random effects models
Hillary M. Heiling, Naim U. Rashid, Quefeng Li +2
Identifying and characterizing relationships between treatments, exposures, or other covariates and time-to-event outcomes has great significance in a wide range of biomedical sett…
glmmPen: High Dimensional Penalized Generalized Linear Mixed Models
Hillary M. Heiling, Naim U. Rashid, Quefeng Li +1
Generalized linear mixed models (GLMMs) are widely used in research for their ability to model correlated outcomes with non-Gaussian conditional distributions. The proper selection…
Efficient Computation of High-Dimensional Penalized Generalized Linear Mixed Models by Latent Factor Modeling of the Random Effects
Hillary M. Heiling, Naim U. Rashid, Quefeng Li +3
Modern biomedical datasets are increasingly high dimensional and exhibit complex correlation structures. Generalized Linear Mixed Models (GLMMs) have long been employed to account…
Deeply-Learned Generalized Linear Models with Missing Data
David K Lim, Naim U Rashid, Junier B Oliva +1
Deep Learning (DL) methods have dramatically increased in popularity in recent years, with significant growth in their application to supervised learning problems in the biomedical…
Unsupervised Imputation of Non-ignorably Missing Data Using Importance-Weighted Autoencoders
David K. Lim, Naim U. Rashid, Junier B. Oliva +1
Deep Learning (DL) methods have dramatically increased in popularity in recent years. While its initial success was demonstrated in the classification and manipulation of image dat…
High dimensional precision medicine from patient-derived xenografts
Naim U. Rashid, Daniel J. Luckett, Jingxiang Chen +8
The complexity of human cancer often results in significant heterogeneity in response to treatment. Precision medicine offers potential to improve patient outcomes by leveraging th…
Modeling Between-Study Heterogeneity for Improved Reproducibility in Gene Signature Selection and Clinical Prediction
Naim U. Rashid, Quefeng Li, Jen Jen Yeh +1
In the genomic era, the identification of gene signatures associated with disease is of significant interest. Such signatures are often used to predict clinical outcomes in new pat…