Using Mobile Phones For Computer Aided Detection Of Anomalies On Chest Radiographs: Proof Of Concept

Abstract Mastering the art of interpreting chest radiographs can be a long and daunting process. We trained a neural network to classify photographs of chest radiographs into 6 groups. The trained model is hosted on a webserver. The model receives and processes photographs of chest radiographs taken using mobile phones. The system then informs the user the most probable diagnosis. Such systems could prove useful in low resource settings which do not have enough highly trained medical personnel and cannot afford the new generation of CAD based radiology equipment.