Random forest prediction of Alzheimer’s disease using pairwise selection from time series data

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

(2018) S.I. Dimitriadis et al.   JOURNAL OF NEUROSCIENCE METHODS

Multivariate Data Analysis and Machine Learning in Alzheimer's Disease with a Focus on Structural Magnetic Resonance Imaging

(2018) Farshad Falahati et al.   JOURNAL OF ALZHEIMERS DISEASE

Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls

(2017) Mohammad R. Arbabshirani et al.   NEUROIMAGE

A review on neuroimaging-based classification studies and associated feature extraction methods for Alzheimer's disease and its prodromal stages

(2017) Saima Rathore et al.   NEUROIMAGE

Structural MRI and Amyloid PET Imaging for Prediction of Conversion to Alzheimer's Disease in Patients with Mild Cognitive Impairment: A Meta-Analysis

(2017) Eun Hyun Seo et al.   Psychiatry Investigation

Random Forest Algorithm for the Classification of Neuroimaging Data in Alzheimer's Disease: A Systematic Review

(2017) Alessia Sarica et al.   Frontiers in Aging Neuroscience

Prediction of AD dementia by biomarkers following the NIA-AA and IWG diagnostic criteria in MCI patients from three European memory clinics

(2015) Annapaola Prestia et al.   Alzheimers & Dementia

Relevant feature set estimation with a knock-out strategy and random forests

(2015) Melanie Ganz et al.   NEUROIMAGE

Machine learning framework for early MRI-based Alzheimer's conversion prediction in MCI subjects

(2015) Elaheh Moradi et al.   NEUROIMAGE

Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: The CADDementia challenge

(2015) Esther E. Bron et al.   NEUROIMAGE

Hierarchical Interactions Model for Predicting Mild Cognitive Impairment (MCI) to Alzheimer's Disease (AD) Conversion

(2014) Han Li et al.   PLoS One

Random Forest ensembles for detection and prediction of Alzheimer's disease with a good between-cohort robustness

(2014) A.V. Lebedev et al.   NeuroImage-Clinical