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Stable Network-Level Functional Connectivity Alterations in Alzheimer's Disease Identified via Interpretable Latent Modelling
2026-01-08
radiology and imaging
Title + abstract only
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Resting-state fMRI provides a non-invasive window into large-scale network-level alterations in Alzheimers disease (AD), but the high-dimensional functional connectivity (FC) and multi-site heterogeneity pose challenges to both classification and interpretabil-ity. We propose an explainable deep-learning framework that combines diagnosis-agnostic latent representation learning with a rigorously nested and interpretable classification pipeline to identify reproducible connectivity biomarkers of A...
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