Research Highlights
We’re interested in developing machine learning algorithms and software to combine sources of Omics and imaging data with an emphasis on discovering novel biological information and biomarkers which can be used for treatment selection in cancer.
From microscope to machine: Overcoming diagnostic challenges with AI innovations
Identification of a Novel Subtype of Endometrial Cancer with Unfavourable Outcome Using Artificial Intelligence-based Histopathology Image Analysis
VOLTA: an Environment-Aware Contrastive Cell Representation Learning for Histopathology
“AI is revolutionizing the field of pathology by offering tools that enhance diagnostic accuracy and efficiency. Despite challenges, advances like AIDA pave the way for AI models to become more adaptable and reliable in real-world clinical settings regardless of location or economic status. By improving the generalisation of AI models, we can bridge the gap in cancer diagnosis and ensure patients receive timely and accurate care.”
AIM Lab
University of British Columbia
2222 Health Sciences Mall, Vancouver, BC V6T 1Z3
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