106 citations · 124 across the 6 of their papers we have counts for
6 papers
Applications of Generative Adversarial Networks in Neuroimaging and Clinical Neuroscience
Rongguang Wang, Vishnu Bashyam, Zhijian Yang +10
Generative adversarial networks (GANs) are one powerful type of deep learning models that have been successfully utilized in numerous fields. They belong to a broader family called…
Robust Hierarchical Patterns for identifying MDD patients: A Multisite Study
Dushyant Sahoo, Mathilde Antoniades, Cynthia H. Y. Fu +1
Many supervised machine learning frameworks have been proposed for disease classification using functional magnetic resonance imaging (fMRI) data, producing important biomarkers. M…
Learning Robust Hierarchical Patterns of Human Brain across Many fMRI Studies
Dushyant Sahoo, Christos Davatzikos
Resting-state fMRI has been shown to provide surrogate biomarkers for the analysis of various diseases. In addition, fMRI data helps in understanding the brain's functional working…
Extraction of Hierarchical Functional Connectivity Components in human brain using Adversarial Learning
Dushyant Sahoo, Christos Davatzikos
The estimation of sparse hierarchical components reflecting patterns of the brain's functional connectivity from rsfMRI data can contribute to our understanding of the brain's func…
Variance Reduced Stochastic Proximal Algorithm for AUC Maximization
Soham Dan, Dushyant Sahoo
Stochastic Gradient Descent has been widely studied with classification accuracy as a performance measure. However, these stochastic algorithms cannot be directly used when non-dec…
Extraction of hierarchical functional connectivity components in human brain using resting-state fMRI
Dushyant Sahoo, Theodore D. Satterthwaite, Christos Davatzikos
The study of hierarchy in networks of the human brain has been of significant interest among the researchers as numerous studies have pointed out towards a functional hierarchical…