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A Study on SARS-CoV-2 (COVID-19) and Machine Learning Based Approach to Detect COVID-19 Through X-Ray Images.

Authors :
Gupta, Anuj Kumar
Sharma, Manvinder
Sharma, Ankit
Menon, Vikas
Source :
International Journal of Image & Graphics; Jul2022, Vol. 22 Issue 3, p1-11, 11p
Publication Year :
2022

Abstract

From origin in Wuhan city of China, a highly communicable and deadly virus is spreading in the entire world and is known as COVID-19. COVID-19 is a new species of coronavirus which is affecting respiratory system of human. The virus is known as severe acute respiratory syndrome (SARS) coronavirus 2 abbreviated as SARS-CoV-2 and generally known as coronavirus disease COVID-19. This is growing day by day in countries. The symptoms include fever, cough and difficulty in breathing. As there is no vaccine made for this virus and COVID-19 tests are not readily available, this is causing panic. Various Artificial Intelligence-based algorithms and frameworks are being developed to detect this virus, but it has not been tested. People are taking advantages of others by providing duplicate COVID-19 test kits. A work is carried out with deep learning to detect presence of COVID 19. With the use of Convolutional Neural networks, the model is trained with dataset of COVID-19 positive and negative X-Rays. The accuracy of training model is 99% and the confusion matrix shows 98% values that are predicted truly. Hence, the model is able to detect the presence of COVID-19. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02194678
Volume :
22
Issue :
3
Database :
Complementary Index
Journal :
International Journal of Image & Graphics
Publication Type :
Academic Journal
Accession number :
157156702
Full Text :
https://doi.org/10.1142/S0219467821400106