Turkish Journal of Computer and Mathematics Education
Journal license

Journal

Turkish Journal of Computer and Mathematics Education


Volume
& Issue

Volume 13, Issue 3


Published
on


Pages

668-680


DOI

Article

Automatic Detection of COVID-19 based in Artificial Intelligence Tools


Authors

Souaad Belhia Affiliation:
Evolutionary Engineering and Distributed Information Systems Laboratory, EEDIS Computer Science Department, University of Sidi Bel Abbes, Algeria
, Souha Al Jahmani Affiliation:
Computer Science Department, University of Sidi Bel Abbes, Algeria
and Reda Adjoudj Affiliation:
Evolutionary Engineering and Distributed Information Systems Laboratory, EEDIS Computer Science Department, University of Sidi Bel Abbes, Algeria


Abstract

The corona virus (COVID-19) spread speedily over the world and eventually became a pandemic. It has had a terrible impact on people's lives, public health, and the global economy. It is vital to find positive cases as soon as workable to prevent the pandemic from spreading further and to treat patients as hurrying as possible. A chest X-ray exam can detect this condition, which should be treated appropriately. Using a multilayer Perceptron (MLP) Neurons Network and a Convolutional Neural Network (CNN). in this study we present an automatic detection approach for COVID-19 infection based on chest X-ray images. The two models are evaluated in two classes, COVID-19 and normal X-ray images, with 95,7% accuracy for MLP model and, 90% accuracy for the CNN model.


Keywords

Artificial Intelligence, COVID-19 (Coronavirus), Detection Approach, MLP Neural Network, X-rays images (CXR), Machine learning, CNN


Citation

Belhia, S., Al Jahmani, S., & Adjoudj, R. (2022). Automatic detection of COVID-19 based in artificial intelligence tools. Turkish Journal of Computer and Mathematics Education, 13(3), 668–680.

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