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arXiv Machine Learning By Proloy Kumar Mondal, Md Kamran Hussin Chowdhury, Hoi Leong Lee

HyperAMS-Net: Adaptive Multi-Scale Spatial Hypergraph Network for Brain Disorder Classification

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HyperAMS‑Net is a deep learning framework that classifies brain disorders from resting‑state fMRI or structural MRI data. It combines adaptive multi‑scale convolution, hypergraph attention, spatial‑channel attention, and adaptive feature fusion to capture complementary patterns across multiple scales and higher‑order dependencies. Evaluated on ABIDE, REST‑meta‑MDD, and ADNI datasets, it achieves state‑of‑the‑art accuracy and AUC, with ablation studies showing hypergraph attention as the most critical component.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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