5 papers
A Heterogeneous Graph Neural Network Fusing Functional and Structural Connectivity for MCI Diagnosis
Feiyu Yin, Yu Lei, Siyuan Dai +4
Brain connectivity alternations associated with brain disorders have been widely reported in resting-state functional imaging (rs-fMRI) and diffusion tensor imaging (DTI). While ma…
Uncertainty Regularized Evidential Regression
Kai Ye, Tiejin Chen, Hua Wei +1
The Evidential Regression Network (ERN) represents a novel approach that integrates deep learning with Dempster-Shafer's theory to predict a target and quantify the associated unce…
Incomplete Multimodal Learning for Complex Brain Disorders Prediction
Reza Shirkavand, Liang Zhan, Heng Huang +2
Recent advancements in the acquisition of various brain data sources have created new opportunities for integrating multimodal brain data to assist in early detection of complex br…
Unified Embeddings of Structural and Functional Connectome via a Function-Constrained Structural Graph Variational Auto-Encoder
Carlo Amodeo, Igor Fortel, Olusola Ajilore +3
Graph theoretical analyses have become standard tools in modeling functional and anatomical connectivity in the brain. With the advent of connectomics, the primary graphs or networ…
Large-scale Collaborative Imaging Genetics Studies of Risk Genetic Factors for Alzheimer's Disease Across Multiple Institutions
Qingyang Li, Tao Yang, Liang Zhan +6
Genome-wide association studies (GWAS) offer new opportunities to identify genetic risk factors for Alzheimer's disease (AD). Recently, collaborative efforts across different insti…