Autism Spectrum Disorder: Review of Datasets, Computational Models, and Future Research Directions

Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorder defined by social, communicative, and behavioral difficulties.Early detection is needed to enhance intervention outcomes but is limited by the drawbacks of standard behavioral assessment.Researches are carried out with different dataset that -structured and unstructured.Innovations that involve video games, smart phones are also growing.This review has investigated various ASD detection and intervention methods, integrating evidence from research studies using neuroimaging, behavioral indicators, multimodal physiological information, and machine learning.The summarization provided in work would help any researcher to understand the rudiments of ASD research and its research gaps.