The WIIH & Ontario NEIHR Indigenizing Health Symposium 2025: Being Safe With Our Culture Again, aims to share knowledges, and foster dialogue and collaboration about Indigenous health and cultural safety. This […]
International learning opportunities can be a critical part of a student's degree while at University of Toronto and expose students to experiences that will enhance their future careers, their appreciation […]
In today's rapidly changing academic publishing environment, researchers and authors face new challenges and opportunities related to copyright management and open access publishing. This webinar aims to equip participants with […]
The Toronto Cannabis and Cannabinoid Research Consortium is co-hosting the Canadian Cannabis Research Summit with the Canadian Consortium for the Investigation of Cannabinoids. The Summit will take place on April […]
The Toronto Cannabis and Cannabinoid Research Consortium is co-hosting the Canadian Cannabis Research Summit with the Canadian Consortium for the Investigation of Cannabinoids. The Summit will take place on April […]
The Centre for Research & Innovation Support (CRIS) presents the next session in the Drawing Across the Disciplines series (https://cris.utoronto.ca/related/drawing-across-the-disciplines/) Generating Images.In this session, we explore how generating images—figures, diagrams, […]
In this class, we are going to take the named entities output from the Named Entity Recognition using LLMs class and apply a statistical model to analyze the data. This […]
Holding a book manuscript workshopoffers a critical opportunity to welcome feedback and input on your near-final book manuscript, strengthening and improvingit before submission to your scholarly press of choice. However, […]
Meet the brilliant minds on the frontlines of Canada’s healthcare revolution. MaRS Impact Health brings together innovators across digital health, medical devices and biotech to commercialize new breakthroughs, empower our […]
In this class, we are going to take the named entities output from the Named Entity Recognition using LLMs class and apply a statistical model to analyze the data. This […]
