Abstract: A method for training a machine learning algorithm that classifies predictive regions-of interest (“ROI”) of progression of idiopathic pulmonary fibrosis. The method includes acquiring a set of computed tomography (CT) images of a plurality of patients and selecting a plurality of ROIs within the set of images. Each of the ROIs designates a label that indicates progression of pulmonary fibrosis and training a machine learning algorithm by inputting the plurality of ROIs and the associated labels into the algorithm. The algorithm identifies the ROIs in the set of images as indicating regions of pulmonary fibrosis within the set of images based on the features.