Automatically identify COVID-19 and Pneumonia patients using Deep learning in Chest X-rays image
1 School of Computer and Information Sciences, University of the Cumberland, Williamsburg, Kentucky, USA.
2 Strayer University, Silver Spring, Maryland, USA.
Research Article
World Journal of Advanced Research and Reviews, 2021, 12(03), 011–019
Publication history:
Received on 28 October 2021; revised on 30 November 2021; accepted on 02 December 2021
Abstract:
At the end of 2019, a new kind of coronavirus (SARS-CoV-2) suffered worldwide and has become the pandemic coronavirus (COVID-19). The outbreak of this virus let to crisis around the world and kills millions of people globally. On March 2020, WHO (World Health Organization) declared it as pandemic disease. The first symptom of this virus is identical to flue and it destroys the human respiratory system. For the identification of this disease, the first key step is the screening of infected patients. The easiest and most popular approach for screening of the COVID-19 patients is chest X-ray images. In this study, our aim to automatically identify the COVID-19 and Pneumonia patients by the X-ray image of infected patient. To identify COVID19 and Pneumonia disease, the convolution Neural Network was training on publicly available dataset on GitHub and Kaggle. The model showed the 98% and 96% training accuracy for three and four classes respectively. The accuracy scores showed the robustness of both model and efficiently deployment for identification of COVID-19 patients.
Keywords:
COVID-19; X-ray imaging; Convolutional neural networks; Feature extraction; Pneumonia Diseases; Deep learning; Lung
Full text article in PDF:
Copyright information:
Copyright © 2021 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0