AI Foundations Lab

BORN’s AI Foundations Lab sits at the intersection of artificial intelligence, population-based data, and perinatal/child health. The Lab combines expertise in machine learning, health informatics, and population-based screening to improve care and outcomes for pregnant individuals and their children.

Co-led by Drs Christine Armour and Kevin Dick, and governed by CHEO’s framework for leading responsibly with AI, the AI Foundations Lab leverages this expertise along with BORN’s population-based data assets (>2 million linkable perinatal/child records for nearly every birth in Ontario since 2012) and on-prem 2-node AI compute cluster to develop and train predictive population health models. As a prescribed registry, BORN is uniquely positioned to also deploy AI models and improve care and outcomes across Ontario, leveraging Prenatal Screening Ontario’s oversight role and by building a digital, interoperable, and intelligent perinatal record for the province.

In addition to applied predictive health modelling, the AI Foundations Lab also addresses central challenges for machine learning models in perinatal and child health:

Outcome rarity: health conditions of interest are often rare by machine learning standards (prevalence <10%).
Trust and equity: integrating explainable AI and equity considerations into modelling frameworks to foster trust and equity
Data privacy and cost-effectiveness: creating integrated, privacy-first AI infrastructure through federated learning, multimodal development, and cryptography

Predictive Algorithms