L2M – Early detection of Gestational Diabetes Mellitus

Gestational diabetes mellitus (GDM) affects up to 20% of pregnancies in Canada and is often diagnosed late, between 24–28 weeks, leaving limited time for preventive action. This delay can lead to serious complications for both mother and child, including preterm birth, macrosomia, and long-term risk of type 2 diabetes. Women with infertility, PCOS, insulin resistance, obesity, or advanced maternal age are particularly vulnerable—yet current screening practices fail to support them early enough. Our project, developed by the MUN Fertility Research Team, addresses this critical gap by introducing a digital health platform that uses AI to predict GDM risk and offer lifestyle interventions as early as preconception or the first trimester. The app collects medical, behavioral, and biometric data—such as age, BMI, physical activity, and sleep patterns—via wearable tech and user input. It then delivers personalized recommendations for physical activity, nutrition, and stress management, alongside behavior-change tools and a peer-support community. Our innovation not only empowers individuals to manage their health proactively but also provides clinicians with a scalable, time-saving tool for improving outcomes in high-risk pregnancies. Postpartum support is included to help reduce future diabetes risk.

Faculty Supervisor:

Katie Wadden

Student:

Partner:

Springboard Atlantic Inc.

Discipline:

Life Sciences

Sector:

Health and Related Sciences & Technology; Artificial Intelligence

University:

Memorial University of Newfoundland

Program: