Smartphone-Captured Chest X-Ray Photographs

Recent research has applied deep learning imaging techniques to detect pulmonary pathology in chest X-rays (CXR) and achieved performance comparable with radiologists on specific lung abnormalities. Industry has managed to deploy such artificial intelligence (AI) solutions in on mobile devices to help clinicians improve their workflow. However, the feasibility of applying these modern AI algorithms to CXR photographs has yet to be evaluated. In this project, 6,453 smartphone photographs were taken from the frontal-view CXR images from two publicly available databases, MIMIC-CXR and CheXpert. We constructed four derivative CXR photograph datasets ( _Photo-MMC, Photo-CXP, Photo-MED, and Photo-DEV_) including photographs taken by several resident doctors and photographs taken with different devices.