Autism Spectrum Disorder Identification Using Machine Learning Models on MRI Data

This study proposes an objective diagnostic method for ASD by extracting quality vectors from multimodal MRI data and applying machine learning and deep learning techniques. A proposed voting ensemble model achieved 95.84% diagnostic accuracy using technical biomarkers from imaging quality metrics derived from the ABIDE II repository.