3 citations · 3 across the 4 of their papers we have counts for
4 papers
Simultaneous Cluster Structure Learning and Estimation of Heterogeneous Graphs for Matrix-variate fMRI Data
Dong Liu, Changwei Zhao, Yong He +3
Graphical models play an important role in neuroscience studies, particularly in brain connectivity analysis. Typically, observations/samples are from several heterogenous groups a…
Joint Learning of Multiple Differential Networks with fMRI data for Brain Connectivity Alteration Detection
Hao Chen, Ying Guo, Yong He +3
In this study we focus on the problem of joint learning of multiple differential networks with function Magnetic Resonance Imaging (fMRI) data sets from multiple research centers.…
Simultaneous Differential Network Analysis and Classification for High-dimensional Matrix-variate Data, with application to Brain Connectivity Alteration Detection and fMRI-guided Medical Diagnoses of Alzheimer's Disease
Chen Hao, Guo Ying, He Yong +6
Alzheimer's disease (AD) is the most common form of dementia, which causes problems with memory, thinking and behavior. Growing evidence has shown that the brain connectivity netwo…
Random Forests of Interaction Trees for Estimating Individualized Treatment Effects in Randomized Trials
Xiaogang Su, Annette T. Peña, Lei Liu +1
Assessing heterogeneous treatment effects has become a growing interest in advancing precision medicine. Individualized treatment effects (ITE) play a critical role in such an ende…