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Found 3 papers, 1 papers with code
Preserving Specificity in Federated Graph Learning for fMRI-based Neurological Disorder Identification
In the personalized branch, we integrate vectorized demographic information (i. e., age, gender, and education years) and functional connectivity networks to preserve site-specific characteristics.
Leveraging Brain Modularity Prior for Interpretable Representation Learning of fMRI
Resting-state functional magnetic resonance imaging (rs-fMRI) can reflect spontaneous neural activities in brain and is widely used for brain disorder analysis. Previous studies propose to extract fMRI representations through diverse machine/deep learning methods for subsequent analysis.
Brain Network Construction and Classification Toolbox (BrainNetClass)
The goal of this work is to introduce a toolbox namely "Brain Network Construction and Classification" (BrainNetClass) to the field to promote more advanced brain network construction methods.
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