On the 15th, a consortium of Yonsei University Industry-Academic Cooperation Foundation and Seoul National University Industry-Academic Cooperation Foundation announced that they will embark on the project 'Enhancement of Big Data on Autism Spectrum Disorder and Development of Digital Medical Devices' organized by the Ministry of Health and Welfare's National Mental Health Center.
About 9.2 billion won of government budget will be invested in this project.
The consortium will be jointly led by Professor Cheon Geun-a of the Department of Child Psychiatry at Yonsei University Severance Hospital and Professor Kim Boong-nyeon of the Department of Child and Adolescent Psychiatry at Seoul National University Hospital, with participation from major domestic medical institutions such as Gangnam Severance Hospital, Gangnam CHA Medical Center, Ewha Womans University Seoul Hospital, Ewha Womans University Mokdong Hospital, Hanyang University Hospital, Wonkwang University Hospital, and Seoul St. Mary's Hospital.
To develop AI-based digital medical devices, technical institutions such as the Department of Biomedical Systems and Informatics at Yonsei University, the Department of Neurosurgery, Korea Institute of Science and Technology (KIST), Urban Data Lab, HuRay Positive, EverTri, Baikal AI, Eco Insight, and adot are also cooperating.
This project aims to develop digital medical devices that support treatment by early screening and predicting the outcomes for high-risk groups of autistic developmental disorders by 2028. To achieve this, a new cohort of 1,200 children under 48 months old will be established, and medical devices will be developed based on the collected data, aiming for designation as an innovative medical device by the Ministry of Food and Drug Safety.
Currently, the diagnosis of autism spectrum disorder heavily relies on the clinical judgment of specialists and the subjective observations of guardians, which has limitations in terms of objectivity and consistency. The medical team's perspective is that by detecting early signals appearing in children's daily lives with digital technology and reflecting them in the screening process, the efficiency of autism spectrum disorder screening can be improved.
Professor Cheon Geun-a, the chief researcher, noted, "The AI-based screening auxiliary medical device for autism spectrum disorder to be developed through this project will serve as a turning point for the paradigm of early diagnosis and treatment of autism."