Chronic obstructive pulmonary disease (COPD) is a 3rd leading cause of death (1) which decreases lung function due to irreversible airway obstruction. The main indicator of the progression of COPD is a rate of the forced expiratory volume of 1 second (FEV1) decline. The intern will build the prediction model for the slope of FEV1 decline and find the genetic variants that affect these FEV1 changes. Some variable selection machine learning algorithms will be applied to screen important genetic variants and the performance of prediction on FEV1 change will be compared. The multi-SNP prediction model can be used to classify individuals who are expected to have a rapid decline of FEV1 based on their genetic information. These pre-screened patients can be targeted for frequent medical examinations.
Providence Health Care
Statistics / Actuarial sciences
Health care and social assistance
University of Victoria
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