67 citations · 95 across the 6 of their papers we have counts for
6 papers
DDS-UDA: Dual-Domain Synergy for Unsupervised Domain Adaptation in Joint Segmentation of Optic Disc and Optic Cup
Yusong Xiao, Yuxuan Wu, Li Xiao +3
Convolutional neural networks (CNNs) have achieved exciting performance in joint segmentation of optic disc and optic cup on single-institution datasets. However, their clinical tr…
MethConvTransformer: A Deep Learning Framework for Cross-Tissue Alzheimer's Disease Detection
Gang Qu, Guanghao Li, Zhongming Zhao
Alzheimer's disease (AD) is a multifactorial neurodegenerative disorder characterized by progressive cognitive decline and widespread epigenetic dysregulation in the brain. DNA met…
Latent Similarity Identifies Important Functional Connections for Phenotype Prediction
Anton Orlichenko, Gang Qu, Gemeng Zhang +5
Objective: Endophenotypes such as brain age and fluid intelligence are important biomarkers of disease status. However, brain imaging studies to identify these biomarkers often enc…
Ensemble manifold based regularized multi-modal graph convolutional network for cognitive ability prediction
Gang Qu, Li Xiao, Wenxing Hu +3
Objective: Multi-modal functional magnetic resonance imaging (fMRI) can be used to make predictions about individual behavioral and cognitive traits based on brain connectivity net…
Distance Correlation Based Brain Functional Connectivity Estimation and Non-Convex Multi-Task Learning for Developmental fMRI Studies
Li Xiao, Biao Cai, Gang Qu +4
Resting-state functional magnetic resonance imaging (rs-fMRI)-derived functional connectivity patterns have been extensively utilized to delineate global functional organization of…
Interpretable multimodal fusion networks reveal mechanisms of brain cognition
Wenxing Hu, Xianghe Meng, Yuntong Bai +7
Multimodal fusion benefits disease diagnosis by providing a more comprehensive perspective. Developing algorithms is challenging due to data heterogeneity and the complex within- a…