Cognitive, Linguistic, and Electrophysiological Performance in Students with and without Reading Disorders

This study aims to analyze the contribution of cognitive, linguistic, and electrophysiological variables to dyslexia in children, using machine learning models. Logistic Regression and Neural Networks models showed good sensitivity and specificity to classify correctly between children with/without dyslexia. Phonological awareness was the main variable contributing to the classification.