You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
(Ongoing Project) Uses CDC data to map the burden of Chronic Obstructive Pulmonary Disorder (COPD) and uses machine learning to determine health factors that may be related to likelihood of its development..
The COPD doctor is a machine learning pipeline that detects whether a patient has gotten COPD by analyzing the input textual descriptions from the patient.
R code for the data management and statistical analysis performed for the project Phenotyping Patients with COPD and Heart Failure: Data from the Swedish Heart Failure Registry
Colocalization analysis of Meconium Ileus Genome-Wide Association Study (GWAS) (Gong et al., 2019) signal around SLC26A9 with spirometry association analysis in the UK Biobank and Spirometa Consortium (Shrine et., 2019) around the same region to elucidate whether there is a shared genetic contribution to disease
Registration of image sets and reference data of inspiratory and expiatory breath-hold CT image pairs acquired from the National Heart Lung Blood Institute COPDgene study archive. This project was developed for a course titled "Medical Image Registration and Applications" - MIRA under MAIA master program.