We develop principled ML methods that turn complex clinical data into actionable insights — improving diagnosis, prognosis, and treatment across real-world patient populations.
Anchored in innovation, health care, and impact modelling; and launched from the University of Calgary.
We build and validate ML models that predict patient risk, disease progression, and treatment response using electronic health records and multimodal data.
Extracting structured knowledge from unstructured clinical notes, radiology reports, and discharge summaries using modern language models.
Federated learning, differential privacy, and synthetic data generation to enable collaborative research without compromising patient confidentiality.
Human-centered design of decision-support tools, studying how clinicians interact with model outputs and how to present uncertainty effectively.
Bridging academic research and real-world impact through partnerships, knowledge transfer, and translational initiatives. Learn more →
Interactive games designed to teach essential first aid skills through engaging, evidence-based scenarios for learners of all levels.
