Danielle D. DeSouza

This paper introduces OViTAD, an optimized vision transformer that predicts Alzheimer's disease stages using resting-state fMRI and structural MRI data, achieving high accuracy with fewer parameters.

The paper identifies three dimensions linking migraine symptoms to brain functional connectivity using CCA and RSFC, revealing novel network targets and patient subtypes.

Caffe LeNet and GoogleNet trained on 2D slices from ADNI scans of adults over 75 report 98.84% to near-perfect accuracy, and 100% per subject for MRI after majority voting.