Predicting the Development of Chronic Lung Disease in Neonataes from Chest X-ray Images Using Deep Learning

Abstract

Neonatal chronic lung disease (CLD) is the most common and serious lung disease in premature infants. No previous studies have used chest X-ray images. In this study, we propose to predict and classify patients with and without CLD from neonatal chest X-ray images using a convolutional neural network (CNN). We conducted a 5-segment cross-validation experiment using chest X-ray images of 115 subjects at 7 days of age. Accuracy and AUC values of 0.6 and 0.642 were obtained, respectively. Future work includes the development of an algorithm suitable for neonatal data and the estimation of other age groups.