Related projects
Discover more projects across a range of sectors and discipline — from AI to cleantech to social innovation.
A quantitative risk prediction model is to be constructed. We need to determine if the available data will fit an existing model and validate the results or if a new statistical model is required. Each case will be allocated into one of three categories (low, moderate and high risk). This stratification must have clinical validity andutility. The cut-offs for the stratification will be established based primarily on clinical utility and on the availability of the data. The cut-offs will be optimized to achieve optimum AUC, NPV, PPV, sensitivity and specificity values. It is expected that a minimal number of variables (2 maximum) will be used in the risk-prediction model for both over fitting and clinical action reasons. This prediction algorithm will allow proteocyte to have in hand an exploratory model to continue its work in developing a robust test that can have clinical utility in stratifying premalignant oral lesions according to the level of risk of progressing to cancer.
Dr. Lehana Thabane
Akram Alyass
Proteocyte Diagnostics Inc.
Epidemiology / Public health and policy
Life sciences
McMaster University
Accelerate
Discover more projects across a range of sectors and discipline — from AI to cleantech to social innovation.
Find the perfect opportunity to put your academic skills and knowledge into practice!
Find ProjectsThe strong support from governments across Canada, international partners, universities, colleges, companies, and community organizations has enabled Mitacs to focus on the core idea that talent and partnerships power innovation — and innovation creates a better future.