Cognitive and intelligence measures for ADHD identification by machine learning models
Adelia-Solás Martínez-Évora, Paula Díaz Marquiegui, Gianluca Susi, Fernando Maestú · FENS Forum 2024
Background: Diagnosing Attention Deficit Hyperactivity Disorder (ADHD) is a challenging process currently focused on questionnaires and clinical interviews, which could be sensitive to subjective biases (Farone et al. 2005). Some studies tried machine learning (ML) algorithms with neurophysiological data such as functional magnetic resonance imaging or electroencephalography to explore objective measures for diagnosing purporses (Mikolas et al. 2022). In this study, ML algorithms are built using cheaper and simpler measures including cognitive and intelligence assessments, reducing time and re
ePoster · Neuroscience