Jan. 21, 2020
New training institute for health-care researchers focuses on a gap in big data
UCalgary part of national program to build equitable artificial intelligence for public health
Big data holds great promise to transform and improve patients’ health-care experience. Artificial intelligence, or AI, and machine learning will give doctors and hospitals access to vast data sets of potentially life-saving information. But limitations in data collection may mean some people are actually at a disadvantage thanks to increased use of these technologies.
Health equity is a critical factor in AI innovation. Marginalized populations — including certain ethnic groups and Indigenous people — are underrepresented in national datasets because Canada does not systematically collect information on these groups in a comprehensive way.
To address this concern, a national institute designed to train emerging public health and computational science researchers in equitable artificial intelligence will be launched this summer by an interdisciplinary team of Canadian scientists, including representatives from the University of Calgary.
Focus on health equity
Using interactive teaching methods, case examples and multidisciplinary team-based learning, the Equitable AI for Public Health (AI4PH): A Focus on Equity and Prevention Summer Institute, will provide participants with an opportunity to gain the expertise and collaborative networks to apply AI methods in their public health research and practice. The institute is funded through a $525,000 grant from the Canadian Institutes of Health Research (CIHR) and will describe how AI methods can be used to address important public health problems while explicitly prioritizing health equity.
"While AI has tremendous potential for public health, biased data frequently hinder health equity. Given that health equity is a principle deeply rooted in public health, the Summer Institute will ensure that our trainees gain not only technical skills but a deep understanding of how to develop equitable AI that can be trusted," says Dr. Joon Lee, PhD, principal investigator on the project and associate professor in the departments of Community Health Sciences and Cardiac Sciences, and member of the O’Brien Institute for Pubic Health and Libin Cardiovascular Institute of Alberta at the Cumming School of Medicine.
AI and public health
Public health uses AI approaches in disease surveillance, but barriers in the lack of specialized training and qualified personnel make it difficult to take advantage of new technologies. The Government of Canada is committed to investing in training opportunities for doctoral, postdoctoral and early career researchers that will build capacity in this crucial area. The AI4PH institute has also acquired sponsorship from CIFAR, aligning with its broader pan-Canadian AI Strategy.
"This is a marquee investment under the CIHR Institute of Population and Public Health's Equitable AI priority area and was designed to ensure that public health not only engages with these new methods, but it also helps lead the conversation on their use to ensure no one is left behind,” says Dr. Steven J. Hoffman, scientific director of CIHR’s Institute of Population and Public Health.
“The AI4PH team has put together an impressive group of collaborators and partners. Their proposal reflects themes foundational to a stellar curriculum on AI and public health and for meeting the needs of a country as diverse as Canada," says Hoffman.
About the institute
The institute’s five principal investigators are: Professors David Buckeridge at McGill University’s School of Population and Global Health; Joon Lee at the University of Calgary’s Cumming School of Medicine; Lisa Lix at the University of Manitoba’s Rady Faculty of Health Sciences; Nathaniel Osgood at the University of Saskatchewan College of Arts and Science; and Laura Rosella at the University of Toronto’s Dalla Lana School of Public Health.
These principal investigators will work with a pan-Canadian team of 23 co-investigators, 16 collaborating faculty scholars, 10 partner institutions, a trainee council and an advisory board.
Upon completion, participants will have a solid understanding of established techniques to develop novel and equitable solutions for the prevention and control of critical public health problems — such as building population-based chronic disease risk prediction models that integrate diverse types of health data — with a high level of ethical rigour.
A pilot version of the institute will be held in Montreal in the summer of 2020, hosted by McGill University and Mila. The second institute will be hosted at the University of Toronto in 2021 and in summer 2022 it will be held at the University of Calgary.
Visit the website for more information, including institute registration.