Machine Learning Diagnosis of Autism Severity Using Physical Fitness and Brain Volume Markers in Children

This study investigates associations between physical fitness, gray matter volume in specific brain regions, and autism severity in 90 children with ASD using machine learning algorithms. The extreme gradient boosting model achieved 77.9% accuracy in diagnosing autism severity, with muscular strength and thalamic brain volume identified as key predictive features.