Title of article :
Automatic detection lung infected COVID-19 disease using deep learning (Convolutional Neural Network)
Author/Authors :
Hakem Alameady, Mali H. Department of Computer Science - Faculty of Computer Science and Maths - University of Kufa, Najaf, Iraq , Fahad, Ahmed University of Thi-Qar, Al-Nassiriya, Iraq , Abdullah, Alaa Education Directorate of Thi-Qar - Ministry of Education, Iraq
Abstract :
In late 2019, a virus appeared suddenly he claims Covid-19, which started in China and began to
spread very widely around the world. and because of its effects, which are not limited to human
life only, but rather in economic and social aspects, and because of the increase in daily injuries
and significantly with the limited hospitals that cannot accommodate these large numbers, it is
necessary to find an automatic and rapid detection method that limits the spread of the disease and
its detection at an early stage in order to be treated more quickly. In this paper, deep learning was
relied upon to create a CNN model to detect COVID-19 infected lungs using chest X-ray images.
The base consists of a set of images taken of lungs infected with Covid-19 disease and normal lungs,
as the CNN structure gave accuracy, Precision, Recall and F-Measure 100%
Keywords :
Deep learning , Convolutional Neural Network , COVID-19
Journal title :
International Journal of Nonlinear Analysis and Applications