[Hinews] SEOUL, South Korea — A groundbreaking artificial intelligence (AI) model developed by a team of South Korean researchers offers a new way to screen for autism spectrum disorder (ASD) using a smartphone, potentially revolutionizing early detection. The project, led by Professors keun-Ah Cheon and Hwiyoung Kim of Severance Hospital along with Professor Bung-Nyun Kim of Seoul National University Hospital, produced an AI tool that analyzes a child’s voice and parental questionnaire responses to assess the likelihood of autism.

Early diagnosis of ASD is critical but often challenging due to subtle initial symptoms. According to the U.S. Centers for Disease Control and Prevention (CDC), one in three children with autism in the United States is not diagnosed until after age 8. Delayed diagnosis can hinder timely interventions, which are crucial for improving outcomes.

The South Korean research team collected data from 1,242 infants and toddlers aged 18 to 48 months across nine hospitals in the country to develop their AI model. The screening process involves parents recording their child’s voice using a smartphone and guiding the child through simple, age-appropriate tasks. These tasks include responding to their name, imitating actions, playing with a ball, engaging in pretend play, or requesting help.

(From left) Professors Keun-Ah Cheon and Hwiyoung Kim of Severance Hospital (Photo courtesy of Severance Hospital)
(From left) Professors Keun-Ah Cheon and Hwiyoung Kim of Severance Hospital (Photo courtesy of Severance Hospital)

The AI integrates the voice data with results from established autism screening tools, such as the Modified Checklist for Autism in Toddlers (M-CHAT), Social Communication Questionnaire (SCQ), and Social Responsiveness Scale-2 (SRS-2). Traditional screening methods typically achieve about 70% accuracy, but integrating AI analysis boosts accuracy to 94%. The model also distinguishes high-risk children from those with confirmed autism diagnoses with 85% accuracy. Furthermore, its predictions showed approximately 80% consistency with the Autism Diagnostic Observation Schedule-2 (ADOS-2), the international gold-standard diagnostic tool.

“By the time families reach a clinic, symptoms are often already severe,” said Professor Cheon. “This AI tool allows for accessible, at-home screening, paving the way for earlier diagnosis and treatment.”

Professor Kim emphasized the tool’s accessibility, noting, “We standardized the tasks so they are easy for all parents to use. This digital tool can provide reliable insights even before a specialist’s diagnosis.”

The research, supported by the National Center for Mental Health’s digital therapeutics development program, was published in the latest issue of npj Digital Medicine, a prestigious peer-reviewed journal.

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