Covid-19 X-Ray Scan Images Classification and Detection by Residual Based Deep Learning

ABSTRACT

Infectious disease Covid-19 is a fast-spreading virus that infects both human beings and animals. As a result of this condition, animals may get infected with the virus. This fatal viral illness has an impact on not only the day-to-day lives of people but also their health and the economy of the nation in which they live. There is currently no vaccination available for COVID-19, regardless of the fact it is a global epidemic that is growing rapidly across the globe. Since then, the virus has swiftly spread over the globe, turning into a pandemic (WHO, 2020), with the number of reported cases and fatalities connected with them continuing to rise on a daily basis. At the moment, more research on an efficient screening technique is necessary in order to diagnose instances of the virus and separate those who have been infected from the rest of the population. To limit the spread of the fatal virus and defend themselves from it, medical practitioners and specialists in many nations across the world are introducing multifunction testingto improve their treatment regimen and testing capacity. This is currently being done to enhance their capacity to detect the infection. When COVID-19-infected patients were studied in a clinical area, it was observed that they were often infected with respiratory illnesses. This conclusion was reached as a result of the findings of the study. Imaging techniques such as chest x- rays (also known as radiography) and chest CT scans are more accurate than other methods when it comes to detecting issues that are connected to the lungs. A thorough chest x-ray is less expensive than a chest CT, albeit. The most successful method of machine learning uses deep learning technologies. This is a great tool for analysing a large number of chest x-ray images, which could significantly affect the Covid-19 screening process. Copyright © 2022, Anka Publishers. All rights reserved.