A Systematic Survey on Artificial Intelligence Based Gesture Centric Behavioral Profiling and Risk Prediction Among Autistic Children

Autism spectrum disorder (ASD) is a neurological and
developmental condition that impairs children's social and cognitive functions, resulting in repetitive behaviors, restricted interests, communication difficulties, and challenges in social interactions.Early detection of ASD may lessen its intensity and persistence. Deeplearning systems can identify ASD earlier than clinics and doctors.Particularly, several studies illustrated practical uses of AI models.Data-centric methodologies may present many challenges about their inconsistency with the conceptual foundation upon which
specialists diagnose ASD. This paper thoroughly analyzed prior research on the use of machine learning and deep learning in the behavioral evaluation of autism spectrum disorder, found prevalent challenges, and proposed critical considerations for the implementation of AI-driven screening and diagnostic systems for ASD in real-world settings. This study will assist researchers,neuropsychiatrists, psychologists, and stakeholders incomprehending ML-based ASD screening and diagnosis.