Deep learning-based prognostication in idiopathic pulmonary fibrosis using chest radiographs

ConclusionsA deep learning model successfully predicted survival in patients with IPF from chest radiographs, comparable to and independent of FVC.Clinical relevance statementDeep learning-based prognostication from chest radiographs offers comparable-to-higher prognostic performance than forced vital capacity.Key Points• A deep learning-based prognostic model for idiopathic pulmonary fibrosis was developed using 6063 radiographs.• The prognostic performance of the model was comparable-to-higher than forced vital capacity, and was independent from FVC in all three external test cohorts.• A modified gender-age-physiology index replacing diffusing capacity for carbon monoxide with the deep learning model showed higher performance than the original index in two external test cohorts.
Source: European Radiology - Category: Radiology Source Type: research