  We propose a deep learning based method for classification of commonly
occurring pathologies in chest X-ray images. The vast number of publicly
available chest X-ray images provides the data necessary for successfully
employing deep learning methodologies to reduce the misdiagnosis of thoracic
diseases. We applied our method to the classification of two example
pathologies, pulmonary nodules and cardiomegaly, and we compared the
performance of our method to three existing methods. The results show an
improvement in AUC for detection of nodules and cardiomegaly compared to the
existing methods.
