Events

Trainee Rounds Presentations (Session 5)

Austin A. Barr: Diffusion-Generated Synthetic Neuroimaging Enables Transfer Learning for Anatomical Landmark Localization in Low-Data Settings

Valentina Tamayo Velasquez: Bringing AI to Psychiatry: Developing and implementing an AI prediction and alerting tool for psychiatric adverse events.

T-CAIREM is pleased to offer this 10-week online, instructor-led professional development course. Participants will get the opportunity to deepen their understanding of AI in medicine. This course provides a comprehensive introduction to data science using Python and uses powerful tools to analyze time-series data, process images, train machine-learning models, and create visualizations. By the end of the course, learners will come away with the skills and mindset needed to delve into tasks ranging from speech analysis to image classification. Registration Deadline: September 8

TITLE: How AI will change medical education delivery: From living curricula to ambient assessment
PRESENTER: Dr. Samir Grover
METHOD: Zoom
DATE: September 15, 2026 (Wed.)
TIME: 12:30pm to 1:30pm ET

Four grants valued at $50,000 are available to researchers advancing AI in health at the University of Toronto (U of T) and Nanyang Technological University (NTU). $25,000 CAD will go to a T-CAIREM PI at the U of T and $25,000 to a C-AIM researcher affiliated with NTU. The grants will advance interdisciplinary AI projects in medicine, engineering, computer science, public health, and/or health systems. APPLICATION DEADLINE: October 2

T-CAIREM's Introduction to AI in Medicine: Practical Issues & Recommendations for Healthcare Professionals weekend mini-course offers practical, hands-on exposure to the tools, opportunities, and implications of AI in your practice. You’ll leave with strategies to improve productivity and insights into the role AI is playing in your specialty. No coding experience is required. This is not a course designed to develop an AI tool. Instead, it focuses on current practical applications of AI in healthcare and their clinical implications. DEADLINE: October 8, 2026