Date: Monday, October 23, 2023
Time: 12:00 p.m. – 1:00 p.m.
Location(s):
NOSM U in Thunder Bay – ATAC6022
NOSM U in Sudbury – MSE322
Learning Objectives:
- The fundamentals of AI methodology.
- How AI has been applied in public health to date.
- How public health practitioners and researchers view the potential of AI to impact public health research and practice.
Speakers:
Dr. Jaky Kueper, Dr. Laura Rosella, Dr. Dan Lizotte
Dr. Jaky Kueper, PhD, is a postdoctoral research associate who recently finished the first combined PhD in epidemiology and computer science at the University of Western Ontario. Her work integrates epidemiology and machine learning to use “everyday data” such as electronic health records to support primary health care and population health. Her PhD research was recognized by a CIHR Banting and Best Doctoral Fellowship and the Governor General’s Gold Medal. She also serves as the TechForward Fellow at the College of Family Physicians of Canada, leading initiatives related to artificial intelligence, family medicine, and compassionate care.
Dr. Laura Rosella, PhD is an Associate Professor in the Dalla Lana School of Public Health, University of Toronto, where she holds the Canada Research Chair in Population Health Analytics and leads the Population Health Analytics Lab, which focuses on developing methods and tools to use population-level data to inform health system decision-making. She holds Inaugural Stephen Family Research Chair in Community Health at the Institute for Better Health, Trillium Health Partners and scientific appointments at Vector AI Institute and the Schwartz Reisman Institute for Technology and Society. In 2021, Dr. Rosella was inducted into the Royal Society of Canada’s College of New Scholars in recognition of international impact in advancing population health. She leads training at the Temerty Centre for Artificial Intelligence Research and Education in Medicine (T-CAIREM) and the Data Sciences Institute at the University of Toronto. Dr. Rosella leads a Pan-Canadian team that launched in 2022 known as AI for Public Health (AI4PH), which is focused on building capacity in AI and big data skills for transformative change in addressing population and public health challenges and understanding how these tools impact health equity
Dr. Dan Lizotte, PhD, is Associate Professor in the Department of Computer Science and the Department of Epidemiology and Biostatistics at The University of Western Ontario. His research aims to support health decision-making by developing and applying machine learning and statistical tools to new sources of data including electronic health records and social media to better support patients and health professionals, particularly in public health and primary health care. His methodological research combines machine learning, optimal sequential decision-making, and multiple objective optimisation. Dr. Lizotte has been formally teaching AI methods to a diverse set of students for over ten years, and he teaches the Public Health Informatics course for in the Schulich Interfaculty Program in Public Health at Western. He is also a member of the Rotman Institute of Philosophy at Western, and he has a strong interest in intersectionality and other critical social theory and how they should inform the development and deployment of AI tools that support health equity. He is currently working with the Alliance for Healthier Communities to develop tools for research and decision support.
This one-credit-per-hour Group Learning program meets the certification criteria of the College of Family Physicians of Canada and has been certified by the Continuing Education and Professional Development Office at the Northern Ontario School of Medicine for up to 1.00 Mainpro+ credits.