Hybrid Deep Learning Model for Autism Spectrum Disorder Diagnosis Using Facial Image Analysis

Researchers evaluated five hybrid deep learning models to improve ASD diagnosis from facial images, addressing limitations of traditional subjective clinical approaches. The MobileNetV2+GRU model achieved 95.5% test accuracy and 98% ROC, demonstrating potential for objective, automated screening support in pediatric settings.