Hierarchical sparse spatiotemporal graph neural network for brain graph classification
Jiaqi Cui, Yuxin Li, Xiran Qu, Yupei Zhang · 2026
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Description
Jiaqi Cui and the team present a neural network for sorting brain graphs from resting brain scans (2026). Such classification can support spotting brain ills. Sparse feature selection is a core difficulty because brain data are large and noisy. Two data sets with 1,956 people in all were used for testing.
The model applies layered lean rules to pick telling features. Spatial graph steps use fixed connection maps, while time steps track changing signals. Scores beat many rival methods, and picked regions were steady. Readable patterns at subnetwork level emerged. The authors offer the framework as a handy tool for robust brain sorting.
Catalog record
| CREATOR | Jiaqi Cui, Yuxin Li, Xiran Qu, Yupei Zhang |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 81 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |