Forecast of COVID-19 by Chest X-Ray Images using CNN Algorithm with Sequential and DenseNet Models

Abstract

The novel Coronavirus (also known as SARS COVID) has led to an unprecedented pandemic, impacting more than 200 countries across the globe. Renowned healthcare environments throughout all the continents have come under acute pressure to face the unknown disease which was declared as a Pandemic by the WHO. Chest X- Rays and CT Scans are more likely to diagnose the pandemic in comparison to the rapid tests in terms of accuracy, better and quicker results. In this paper, a Machine Learning technique based on a Convolutional Neural Network (CNN) using Sequential and DenseNet models is being presented to detect COVID-19 among patients using real-time data. The proposed system scrutinizes chest X-Ray images to recognize the patients who are really prone to the novel coronavirus. The results designate that this idea comes handy in diagnosing the pandemic; X- Rays are the best and easiest possible way to work upon and provide admirable results within less time.