The chest X-Ray examination is the most important part in diagnosing the human lung diseases, thus the chest x-ray must be diagnosed carefully by the specified doctors to make sure that the right diagnosis is made, so for achieving speed in this process and gaining accurate results the automation of report creation and diseases diagnose is a must due to doctors having too much work and they’re not distributed on the same locations all the time , so we are presenting a web-based solution for the diagnosis of chest x-ray , using artificial intelligence specifically, deep learning models, so we are making use the vivid hospital and radiology centers x-rays database which have been left unused, and by presenting this project we facilitate the process of diagnosis and report generation , so that it's easier for doctors and patients. Deep Learning Model

The chest X-ray is one of the most commonly accessible radiological examinations for screening and diagnosis of many lung diseases. A tremendous number of X-ray imaging studies accompanied by radiological reports are accumulated and stored in many modern hospitals’ Picture Archiving and Communication Systems (PACS). On the other side, it is still an open question how this type of hospital-size knowledge database containing invaluable imaging informatics (i.e., loosely labeled) can be used to facilitate the data-hungry deep learning paradigms in building truly large-scale high precision computeraided diagnosis (CAD) systems.