for the Alzheimer's Disease Neuroimaging Initiative

Deep learning reveals Alzheimer's disease onset in MCI subjects: Results from an international challenge

Nicola Amoroso, Domenico Diacono, Annarita Fanizzi, 2017, Journal of Neuroscience Methods.

Ensemble of random forests One vs. Rest classifiers for MCI and AD prediction using ANOVA cortical and subcortical feature selection and partial least squares

for the Alzheimer's Disease Neuroimaging Initiative, J. Ramírez, Francisco J. Martínez-Murcia, 2017, Journal of Neuroscience Methods.

Clustering-based multi-view network fusion for estimating brain network atlases of healthy and disordered populations

Islem Rekik, for the Alzheimer's Disease Neuroimaging Initiative, Salma Dhifallah, 2019, Journal of Neuroscience Methods.

Random forest feature selection, fusion and ensemble strategy: Combining multiple morphological MRI measures to discriminate among healhy elderly, MCI, cMCI and alzheimer’s disease patients: From the alzheimer’s disease neuroimaging initiative (ADNI) database

for the Alzheimer's Disease Neuroimaging Initiative, Dimitris Liparas, S. I. Dimitriadis, 2017, Journal of Neuroscience Methods.

A Novel Texture Extraction Technique with T1 Weighted MRI for the Classification of Alzheimer’s Disease

for the Alzheimer's Disease Neuroimaging Initiative, Latha Parthiban, Krishnakumar Vaithinathan, 2019, Journal of Neuroscience Methods.