Machine learning Classification of Dyslexic Children based on EEG Local Network Features

Abstract
Machine learning can be used to find meaningful patterns characterizing individual differences. Deploying a machine learning classifier fed by local features derived from graph analysis of electroencephalographic (EEG) data, we aimed at designing a neurobiologically-based classifier to differentiate two groups of children, one group with and the other group without dyslexia, in a robust way. We used EEG resting-state data of 29 dyslexics and 15...
Paper Details
Title
Machine learning Classification of Dyslexic Children based on EEG Local Network Features
Published Date
Mar 6, 2019
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