News

Med-i CREATE Students Present Research to Visiting Scholar

Med-i CREATE Students Present Research to Visiting Scholar

Med-i CREATE students had the opportunity to present their research work to Dr. Molly Shoichet, Annual Dr. Andrew and Margaret Bruce Visiting Scholar. Dr. Shoichet is currently a University Professor and Michael E. Charles Chair in Chemical Engineering at the University of Toronto, where her research is focused on drug and cell delivery strategies in the central nervous system (brain, spinal cord, retina) and...
Med-i CREATE Students Led a Thought-Provoking Debate at ImNo Symposium

Med-i CREATE Students Led a Thought-Provoking Debate at ImNo Symposium

The 22nd ImNo Symposium took place in Mississauga from March 19-20, 2024. At the heart of the symposium was a dynamic debate led by students from the Med-i CREATE program, in collaboration with the students from CREATE program in Responsible AI at Toronto Metropolitan University. The debate tackled the theme, "Recent developments in AI present exciting opportunities for improving the...

Rohan Khan Talks about Algorithmic Bias and Fairness

In a recent seminar organized by the Queen's School of Computing as part of The Social, Ethical, and Legal Issues in Computing Lecture Series, Rohan Khan, a Med-i CREATE doctoral student, talked about the intricate realm of algorithmic bias and fairness. Her presentation, titled "Algorithmic Bias and Fairness: Exploring Historical Context, Methodological Shortcomings, and Future Challenges," looked closely at important...
Zhendong Sha Successful Ph.D. Defense

Zhendong Sha Successful Ph.D. Defense

Zhendong Sha, a Med-i CREATE student completed his Ph.D. defense in December 2023. He was supervised by Dr. Ting Hu. Congratulations Zhendong! Visit MIB@Queen's for information

Projects

Integration, federation, and retrieval of large-scale data repositories in Canada

We collaborate with the Canadian Institute of Health Information (CIHI) and the Ontario Health Data Platform (OHDP) to tackle novel challenges in data management and devise evaluation frameworks that center on security, performance and fairness.

Next generation of actionable prescriptive analysis using multi-resolution, multi-modality data

We build computation models of disease from multi-omics data using machine learning, deep learning and evolutionary algorithms, focusing on innovations that address the unique nature of health data and the unavailability and vagueness of gold-standard labels (e.g., pathology labels).

Democratization of AI, software and data for healthcare

We're international leaders in developing and disseminating open source software using low-cost point-of-care imaging. Our positive impact on the global computer–assisted medical interventions community has is constantly expanding. We'll meet new challenges for discovery, refinement of methods and innovative AI-powered solutions using large open source data, hence democratizing access to care and positive outcomes of AI.