Ajay S. Kurani

This paper introduces geometric deep learning frameworks for analyzing brain morphology in Alzheimer's disease, showing improved classification and morphological insights compared to prior methods.

This paper shows that small effect sizes in resting-state fMRI studies lead to reproducibility issues, even after multiple comparison corrections, and recommends meta-analysis of un-thresholded data for better results.