Investigation of Eye-Tracking Scan Path as a Biomarker for Autism Screening Using Machine Learning Algorithms.

ABSTRACT: Autism spectrum disorder is a group of disorders marked by difficulties with social skills, repetitive activities, speech, and nonverbal communication. Deficits in paying attention to, and processing, social stimuli are common for children with autism spectrum disorders. It is uncertain whether eye-tracking technologies can assist in establishing an early biomarker of autism based on the children's atypical visual preference patterns. In this study, we used machine learning methods to test the applicability of eye-tracking data in children to aid in the early screening of autism. We looked into the effectiveness of various machine learning techniques to discover the best model for predicting autism using visualized eye-tracking scan path images. We adopted three traditional machine learnin

SUBMITTER: Kanhirakadavath MR 

PROVIDER: S-EPMC8871384 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature