Automated AI based identification of autism spectrum disorder from home videos.

ABSTRACT: Autism spectrum disorder (ASD) is a prevalent childhood-onset neurodevelopmental condition. Early diagnosis remains challenging by the time, cost, and expertise required for traditional assessments, creating barriers to timely identification. We developed an AI-based screening system leveraging home-recorded videos to improve early ASD detection. Three task-based video protocols under 1 min each-name-response, imitation, and ball-playing-were developed, and home videos following these protocols were collected from 510 children (253 ASD, 257 typically developing), aged 18-48 months, across 9 hospitals in South Korea. Task-specific features were extracted using deep learning models and combined with demographic data through machine learning classifiers. The ensemble model achieved an area un

SUBMITTER: Kim DY 

PROVIDER: S-EPMC12514021 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature