3 citations · 4 across the 4 of their papers we have counts for
4 papers
Penalized model-based clustering of fMRI data
Andrew DiLernia, Karina Quevedo, Jazmin Camchong +3
Functional magnetic resonance imaging (fMRI) data have become increasingly available and are useful for describing functional connectivity (FC), the relatedness of neuronal activit…
Multi-resolution Super Learner for Voxel-wise Classification of Prostate Cancer Using Multi-parametric MRI
Jin Jin, Lin Zhang, Ethan Leng +2
While current research has shown the importance of Multi-parametric MRI (mpMRI) in diagnosing prostate cancer (PCa), further investigation is needed for how to incorporate the spec…
Bayesian Spatial Models for Voxel-wise Prostate Cancer Classification Using Multi-parametric MRI Data
Jin Jin, Lin Zhang, Ethan Leng +2
Multi-parametric magnetic resonance imaging (mpMRI) plays an increasingly important role in the diagnosis of prostate cancer. Various computer-aided detection algorithms have been…
A random covariance model for bi-level graphical modeling with application to resting-state fMRI data
Lin Zhang, Andrew DiLernia, Karina Quevedo +3
This paper considers a novel problem, bi-level graphical modeling, in which multiple individual graphical models can be considered as variants of a common group-level graphical mod…