Frank A. Provenzano

The paper links entorhinal cortex-tentorial proximity to tau burden and dementia progression using multimodal imaging data from ADNI.

The paper reports clinical phenotypes and longitudinal adaptive function in KIF1A-associated neurological disorder and correlates them with computational predictions of genotype severity.

This study uses patient-derived forebrain organoids to investigate the effects of a CNTNAP2 mutation on cortical development, finding increased cell proliferation and differential gene expression associated with ASD.

This paper develops a deep learning model using MRI to classify Alzheimer’s disease and finds it outperforms traditional biomarkers in detecting prodromal disease and predicting progression.

This study applies 3D CNNs to MRI data to classify Alzheimer’s disease, showing high accuracy and identifying the hippocampal formation as a key predictive region.