Connectomics in NeuroImaging

<p>Unsupervised Feature Selection via Adaptive Embedding and Sparse Learning for Parkinson's Disease Diagnosis.- A Novel Graph Neural Network to Localize Eloquent Cortex in Brain Tumor Patients from Resting-State fMRI Connectivity.- Graph Morphology-Based Genetic Algorithm for Classifying Late Dementia States.- Covariance Shrinkage for Dynamic Functional Connectivity.- Rapid Acceleration of the Permutation Test via Transpositions.- Heat kernels with functional connectomes reveal atypical energy transport in peripheral subnetworks in autism.- A Mass Multivariate Edge-wise Approach for Combining Multiple Connectomes to Improve the Detection of Group Differences.- Adversarial Connectome Embedding for Mild Cognitive Impairment Identification using Cortical Morphological Networks.- A Machine Learning Framework for Accurate Functional Connectome Fingerprinting and an Application of a Siamese Network.- Test-Retest Reliability of Functional Networks for Evaluation of Data-Driven Parcellation.- Constraining Disease Progression Models Using Subject Specific Connectivity Priors.- Hemodynamic Matrix Factorization for Functional Magnetic Resonance Imaging.- Network Dependency Index Stratified Subnetwork Analysis of Functional Connectomes: An application to autism.</p>