multi disease detector app using chest x-ray

computer engineering

Nowadays, Covid-19 is the most important disease that affects daily life globally. Therefore, many methods have been offered to fight against Covid-19. In this paper, a convolutional neural network algorithm approach was introduced for Covid-19 detection which is an image classification algorithm. Since Covid-19 disease is similar to pneumonia, three classes of data sets such as Covid-19, pneumonia, and normal chest x-ray images were employed in this study. The android app system acts as a disease detector; for every input x-ray image given to the system, the output is generated as information regarding the disease. This android app provides information about covid19, pneumonia, normal, and classifies between two diseases. This System gives information about a particular disease that has been detected through a chest x-ray digital image and shows it within seconds by using our trained model. We merge the android app with deep learning. This app doesn't require the internet for the feature of image classification and personal information is not compulsory. This app is cost-effective. The COVID-19 coronavirus has spread rapidly around the world and has caused global panic. Chest x-ray images can play a major role in confirming positive COVID-19 patients and this can be a faster alternative before getting tested with an RTPCR test within a short duration.

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