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Ditching predefined functional sub-networks unlocks state-of-the-art brain disorder diagnosis by learning hierarchical brain network organization directly from fMRI data.
BrainSTR disentangles subtle disease signatures in dynamic brain networks by explicitly modeling spatio-temporal dependencies with contrastive learning, revealing interpretable biomarkers for neuropsychiatric disorders.
