About this Event
The pandemic has cast a light on the essential role of medical science as an arbiter for the well-being of Canadians. However, this spotlight has shown that several inequities exist in medical research and practices. Biases can seep into health data collection leading to unequal conclusions on disease severity. Hospital and university leaders who coordinate health policy responses are not necessarily reflective of the population's diversity leading to misrepresentation. Raw Talk Live 2022 will deliver a panel discussion with a two-fold purpose. First, we will highlight how bias enters health data leading to inequitable health outcomes. Second, we will showcase the need for diversity in medicine and how diversity improves patient experience and health outcomes amongst marginalized populations.
Afterwards, take the time to network with our panelists and your peers as we host our first in-person event in more than two years!
Raw Talk Live 2022 timeline:
5:00-6:00 pm - Registration
6:00-7:00 pm - Panel Discussion
7:00-9:00 pm - Open networking/Break/Dinner
Nida Shah (Instagram and Twitter: @Epidtalks )
Nida Shah is a public health professional working to transform health systems through evidence generation, digital health innovation and implementation science. Based out of SickKids, she oversees a portfolio of innovative research projects anchored in long-term pediatric cancer survivorship care in partnership with Ontario Health and The Pediatric Oncology Group of Ontario. Further, Nida has spent 3 years in Chicago during her training working on healthcare delivery endeavours to bridge access inequities in vulnerable populations. She continues to engage in advocacy work in the Greater Toronto Area and has joined panels with Peel government and health officials throughout the pandemic to emphasize the importance of bridging social inequities within the population.
Dr. Pascal Tyrell (Twitter: @pascaltyrrell; Instagram: @Tyrrell4innovation; Linkedin: https://www.linkedin.com/in/tyrrell4innovation/)
Pascal Tyrrell is a data scientist—a combination of research methodologist, computer/database solutions architect and innovator. He is the director of data science and associate professor with the Department of Medical Imaging, University of Toronto where he is the founder of the MiDATA data science program. Pascal is also appointed to the Institute of Medical Science and the Department of Statistical Sciences where his research aims to establish useful guidelines for the quantity and quality of input data for machine learning in medical imaging research. Pascal is a serial entrepreneur with experience in the computer, financial, and medical device industries.
Heather Krause (Twitter: @datassist; Website: https://weallcount.com/)
Heather Krause, PStat is a data scientist with over a decade of experience building tools that improve practices and systems. Heather is a statistician with years of experience working on complex data problems and producing real-world knowledge. She has a strong love of finding data, analyzing it in creative ways and using cutting edge visualization methods to visualize the results. Her emphasis is on combining strong statistical analysis with clear and meaningful communication. She is currently working on implementing tools for equity and ethics in data. As the founder of two successful data science companies, she attacks the largest questions facing societies today, working with both civic and corporate organizations to improve outcomes and lives. Her relentless pursuit of clarity and realism in these projects pushed her beyond pure analysis to mastering the entire data ecosystem including award-winning work in data sourcing, modeling, and data storytelling, each incorporating bleeding edge theory and technologies. Her work proves that data narratives can be meaningful to any audience from a boardroom to the front page. Heather is the founder of We All Count, a project for equity in data working with teams across the globe to embed a lens of ethics into their data products from funding to data collection to statistical analysis and algorithmic accountability. Her unique set of tools and contributions have been sought across a range of clients from MasterCard and Wells Fargo to the United Nations, the Canadian Government, and the Bill and Melinda Gates Foundation. She is on the Data Advisory Board of the UNHCR.
Event Venue & Nearby Stays
Faculty Club - University Of Toronto, 41 Willcocks Street, Toronto, Canada