Using Artificial Intelligence to Save Lives at Birth

Abstract: 

I will talk about the vision, motivation, as well as the design and development of Ubenwa, an AI-driven technology to provide global access to early diagnosis of birth asphyxia. Birth asphyxia is one of the top 3 causes of newborn mortality today. Ubenwa aims democratise access to clinical-grade screening through a mobile tool that is non-invasive, swift, easy to use and cost effective.

Bio: 

Charles is a PhD candidate at McGill University and Mila - the Québec AI Institute. He is interested in the design and development of improved diagnostic and decision-making tools in healthcare. He leads the Ubenwa Health, a collaboration between researchers in Canada and Nigeria, developing low-cost, AI-powered mobile app for the diagnosis of perinatal asphyxia from the infant cry. At the Montreal Children's Hospital, Charles is involved in the APEX project, where he has been developing machine learning algorithms for analyzing cardiorespiratory behaviour of preterm newborns in order to determine their readiness for extubation. He has worked with Health Experiences Research Canada contributing to the design and leading the development of the HERS mobile app - a personalized recommendation tool for breast cancer patients. Charles is a Jeanne Sauvé Fellow and a Vanier Doctoral Scholar.