260 citations · 963 across the 66 of their papers we have counts for
4 papers · 2 filters
Normative Modeling via Conditional Variational Autoencoder and Adversarial Learning to Identify Brain Dysfunction in Alzheimer's Disease
Xuetong Wang, Kanhao Zhao, Rong Zhou +4
Normative modeling is an emerging and promising approach to effectively study disorder heterogeneity in individual participants. In this study, we propose a novel normative modelin…
Tensor-Based Multi-Modality Feature Selection and Regression for Alzheimer's Disease Diagnosis
Jun Yu, Zhaoming Kong, Liang Zhan +2
The assessment of Alzheimer's Disease (AD) and Mild Cognitive Impairment (MCI) associated with brain changes remains a challenging task. Recent studies have demonstrated that combi…
Data-Efficient Brain Connectome Analysis via Multi-Task Meta-Learning
Yi Yang, Yanqiao Zhu, Hejie Cui +4
Brain networks characterize complex connectivities among brain regions as graph structures, which provide a powerful means to study brain connectomes. In recent years, graph neural…
Interpretable Graph Convolutional Network of Multi-Modality Brain Imaging for Alzheimer's Disease Diagnosis
Houliang Zhou, Lifang He, Yu Zhang +2
Identification of brain regions related to the specific neurological disorders are of great importance for biomarker and diagnostic studies. In this paper, we propose an interpreta…