Deep Learning of Resting-state Electroencephalogram Signals for 3-class Classification of Alzheimer’s Disease, Mild Cognitive Impairment and Healthy Ageing

Autor: Huggins, Cameron J, Escudero, Javier, Parra, Mario A, Scally, Brian, Anghinah, Renato, Lacerda de Araújo, Amanda Vitória, Basile, Luis F, Abasolo, Daniel

Publikováno v: Huggins, C J, Escudero, J, Parra, M A, Scally, B, Anghinah, R, Lacerda de Araújo, A V, Basile, L F & Abasolo, D 2021, ' Deep Learning of Resting-state Electroencephalogram Signals for 3-class Classification of Alzheimer’s Disease, Mild Cognitive Impairment and Healthy Ageing ', Journal of Neural Engineering . https://doi.org/10.1088/1741-2552/ac05d8

Objective: This study aimed to produce a novel Deep Learning (DL) model for the classification of subjects with Alzheimer’s Disease (AD), Mild Cognitive Impairment (MCI) subjects and Healthy Ageing (HA) subjects using resting-state scalp EEG signal

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______3094::f68ac759f5e4a1521c86f09c011997f0
https://www.pure.ed.ac.uk/ws/files/212057341/211270275_AFPRM.pdf

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