Mobile-based Application for COVID-19 Detection from Lung X-Ray Scans with Artificial Neural Networks (ANN)

In early 2020, the World Health Organization (WHO) identified a novel coronavirus referred to as SARS-CoV-2, which is associated with the now commonly known COVID-19 disease. COVID-19 was shortly later characterized as a pandemic. All countries around the globe have been severely affected and the disease has accumulated a total of over 200 million cases and more than five million deaths in the past two years. Symptoms associated with COVID-19 vary greatly in severity. Some infected with COVID-19 are asymptomatic, while others experience critical disease with life-threatening complications. In this paper, a mobile-based application has been created to help classify Covid-19 and non-Covid-19 lung when given an image of a Chest X-Ray (CXR). A variety of different artificial neural networks (ANN) including our baseline model, InceptionV3, MobileNetV2, MobileNetV3, VGG16, and VGG19 were tested to see which would provide the optimal results. It is concluded that MobileNetV3 gives the best test accuracy of 95.49% and is considered a lightweight model suitable for a mobile-based application.