Utilising 3 Deep Learning Models for Outcome Prediction in Patients With Idiopathic Pulmonary Fibrosis

Severity of traction bronchiectasis, when scored visually, is a powerful predictor of mortality in patients with fibrotic lung disease but technical challenges have made the development of automated methods for objective, reproducible quantification of this sign, difficult. We aimed to investigate the prognostic utility of a novel deep-learning algorithm for quantifying the severity of traction bronchiectasis in patients with idiopathic pulmonary fibrosis (IPF) enrolled in the AustralianIPF Registry.