Can AI Help Identify Babies at Risk of Autism?

BORN is pleased to share a new podcast episode, Can AI Help Identify Babies at Risk of Autism?, featuring Dr. Christine Armour, Co-Medical Director of Prenatal Screening Ontario (PSO) using data from Better Outcomes Registry and Network (BORN) Ontario.

In the episode, Dr. Armour discusses research exploring whether patterns in prenatal ultrasound data—analyzed using artificial intelligence (AI)—could help identify babies who may be at increased risk for autism spectrum disorder (ASD). She offers insight into how AI could support earlier identification and diagnosis, potentially giving families and health care providers more time to plan for early support and services. Dr. Armour also highlights the importance of approaching this work responsibly, using CHEO’s framework for responsible AI, and raises key questions about ethics, privacy, and how this type of information might be used in real-world health care.

Whether you’re a parent, provider, researcher, or simply curious about how AI is being used in health care, the conversation offers insight into a complex and rapidly evolving area.

This research is made possible through the use of population-level health data from BORN Ontario, ICES, and CIHI and was conducted in ICES’ Health AI Data Analytics Platform. This research was performed by Dr. Kevin Dick, AI Data Scientist at BORN, along with Drs. Mark Walker and Stephen Hawken. The project is funded by CHEO’s Precision Child and Youth Mental Health (PCYMH) Collaboratory, which supports new approaches to better understand and improve mental health outcomes for children and youth.