ASD Diagnoses using Deep Learning and Neuroimaging as A Biomarker: A Review

Authors

Sonali Beri
Dept. of Electronics and communications engineering Dr. B. R. Ambedkar National Institute of Technology Jalandhar, Punjab, India
Arun Khosla
Dept. of Electronics and communications engineering Dr. B. R. Ambedkar National Institute of Technology Jalandhar, Punjab, India

Synopsis

Autism Spectrum Disorder (ASD) is a commonly occurring neurodevelopmental disorder characterized by problems occurring in social communication and the presence of restricted and repetitive behavior and interests. Up to now, ASD is being diagnosed considering clinical interview, behavior and developmental factors. Early diagnosis of it can help the autistic people to deal well in their lives. For this early detection different biomarker like Neuro-imaging data can be used which includes structural and functional magnetic resonance imaging. In order to explore the functional and structural differences in between TC and autistic group deep learning methods can be used. These deep learning methods will help in efficient classification and thus can help in autism diagnosis as well. In this paper studies related to various Deep Learning techniques used to diagnose autism are being looked at.

WREC21
Published
September 22, 2021
Online ISSN
2582-3922