A Comprehensive Analysis of AI-Based Approaches for Autism Detection and Classification

This review examines the application of artificial intelligence in early autism detection across multiple modalities including eye tracking, facial expression analysis, motor skill assessment, and neuroimaging (MRI/fMRI/EEG). The paper synthesizes recent advances in AI-based autism classification while discussing both successes and challenges in implementing these technologies for improved early identification and intervention outcomes.