THE UNIVERSITY OF BRITISH COLUMBIA
Lung Function Predictor for the General Population
This web application uses a linear mixed effects predictive model based on the Framingham Offspring Study to predict lung function decline over time in healthy adult population. Predictions are based on twenty common predictors selected through machine learning selection, and random effects to model unexplained heterogeneity among individuals.
Please read usage terms at http://ipress.resp.med.ubc.ca/FraminghamFEV1/disclaimer.html
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This CIHR-funded project aims at devloping and validating prediction tools for precision disease management for COPD, and implementing such tools as Web Apps to be freely accessible to the patient and care provider community.
EPIC is a comprehensive epidemiologic and decision-analytic model for chronic obstructive pulmonary disease (COPD) in Canada.
Our group is actively in both applied research in developing PRecision Medicine tools for better decision making for clinical care of both asthma and COPD. We have also contributed to the methodology of Clinical Prediction Modeling.