Novel Mechanism to Predict and Detect nCOVID-19 Using Deep Learning with Convolutional Neural Networks: An Holistic Approach

Abstract

Deep learning is nowadays being widely employed in the medical field to ease several tasks which are required to confront with several serious diseases spreading across the world. Today, the world is fighting with such a severe disease of novel coronavirus, also known as nCOVID-19. Although a number of techniques and approaches exist to detect this disease, but all these techniques utilize manual work and consume lot of effort and time. Thus, so as to increase the pace at which the nCOVID-19 can be detected within an individual, deep learning has a great role to play which utilizes convolutional neural network (CNN) to detect it by examining the X-ray picture of the chest of the person. nCOVID-19 is a pandemic virus that has affected millions of people and resulted in casualties of more than 1,140,000 people as of October 24, 2020. Several metrics in this paper have been used to predict the performance, i.e., accuracy, sensitivity, specificity, and precision. This research presents the critical breakthrough for the automated discovery of the nCOVID-19 which has employed the datasets from the public machine learning repositories, including Kaggle, UCI, and GitHub.