Amage-net

1. Amage-net predicts brain age in silico (MAE 5.09, RMSE 6.52, R2 0.87, PCC 0.94).

   “achieving a mean absolute error (MAE) of 5.09, root mean square error (RMSE) of 6.52, R 2 of 0.87, and Pearson correlation (PCC) of 0.94.”

   In silicon = 652

   Attention-Guided Multimodal Neuroimaging Fusion Network for Modeling Brain Aging Pattern

   bioRxiv (Cold Spring Harbor Laboratory)·31 Mar 2026Preprint

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