Random Forest Algorithm for the Classification of Neuroimaging Data in Alzheimers Disease: A Systematic Review

Autor: Sarica Alessia 1, Cerasa Antonio 1, Quattrone Aldo 1, 2

Publikováno v: Frontiers in aging neuroscience 9 (2017): 329. doi:10.3389/fnagi.2017.00329
info:cnr-pdr/source/autori:Sarica Alessia 1, Cerasa Antonio 1, Quattrone Aldo 1,2/titolo:Random Forest Algorithm for the Classification of Neuroimaging Data in Alzheimer's Disease: A Systematic Review/doi:10.3389%2Ffnagi.2017.00329/rivista:Frontiers in aging neuroscience/anno:2017/pagina_da:329/pagina_a:/intervallo_pagine:329/volume:9
Frontiers in Aging Neuroscience
Frontiers in Aging Neuroscience, Vol 9 (2017)

Objective: Machine learning classification has been the most important computational development in the last years to satisfy the primary need of clinicians for automatic early diagnosis and prognosis. Nowadays, Random Forest (RF) algorithm has been

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