• 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

  • Pages
    9
  • From page
    921
  • To page
    929
  • 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
  • Serial Year
    2021
  • Record number

    2701660