Machine Learning to Predict Temporomandibular Disorders Risk from Genotypes

The goal of this project is to develop new machine learning methods and computational strategies to mega-analyze data from well-characterized datasets on chronic pain conditions to develop a genetic predictive tool. This tool will be implemented in an online interactive dashboard and used by the Quebec Pain Research Network (QPRN) community. This collaboration with Plotly will make the developed machine learning models more accessible to applied researchers by: 1) visualizing the genetic effects which drive the predictions, 2) allowing users to interactively generate new predictions over a range of parameters and visually compare the outputs, and, 3) producing different graphics of the data to reveal details that might be hidden by summary statistics.

Intern: 
Kai Yang;Jesse Islam;Julien St-Pierre
Faculty Supervisor: 
Sahir Bhatnagar
Province: 
Quebec
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