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Authors: Isabel Heloíse Santos Silva 1 ; Ramoni Reus Barros Negreiros 1 ; André Luiz Firmino Alves 1 ; 2 ; Dalton Cézane Gomes Valadares 3 ; 2 ; 4 and Angelo Perkusich 2 ; 4

Affiliations: 1 Federal Institute of Paraíba (IFPB), Picuí, PB, Brazil ; 2 Federal University of Campina Grande, Computer Science, Campina Grande, PB, Brazil ; 3 Federal Institute of Pernambuco, Mechanical Engineering Department, Caruaru, PE, Brazil ; 4 VIRTUS RDI Center, Campina Grande, PB, Brazil

Keyword(s): Artificial Neural Networks, ANNs, Machine Learning, Image-based Diagnosis, Radiographic Images.

Abstract: The new coronavirus pandemic has brought disruption to the world. One of the significant dilemmas to be solved by countries, especially in underdeveloped countries like Brazil, is the lack of mass testing for the population. An alternative to these tests is detecting the disease through the analysis of radiographic images. To process different types of images automatically, we employed deep learning algorithms to achieve success in recognizing different diagnostics. This work aims to train a deep learning model capable of automatically recognizing the Covid-19 diagnosis through radiographic images. Comparing images of coronavirus, healthy lung, and bacterial and viral pneumonia, we obtained a result with 94% accuracy.

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Paper citation in several formats:
Silva, I.; Negreiros, R.; Alves, A.; Valadares, D. and Perkusich, A. (2022). Classification of Chest X-ray Images to Diagnose Covid-19 using Deep Learning Techniques. In Proceedings of the 19th International Conference on Wireless Networks and Mobile Systems - WINSYS; ISBN 978-989-758-592-0; ISSN 2184-948X, SciTePress, pages 93-100. DOI: 10.5220/0011339700003286

@conference{winsys22,
author={Isabel Heloíse Santos Silva. and Ramoni Reus Barros Negreiros. and André Luiz Firmino Alves. and Dalton Cézane Gomes Valadares. and Angelo Perkusich.},
title={Classification of Chest X-ray Images to Diagnose Covid-19 using Deep Learning Techniques},
booktitle={Proceedings of the 19th International Conference on Wireless Networks and Mobile Systems - WINSYS},
year={2022},
pages={93-100},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011339700003286},
isbn={978-989-758-592-0},
issn={2184-948X},
}

TY - CONF

JO - Proceedings of the 19th International Conference on Wireless Networks and Mobile Systems - WINSYS
TI - Classification of Chest X-ray Images to Diagnose Covid-19 using Deep Learning Techniques
SN - 978-989-758-592-0
IS - 2184-948X
AU - Silva, I.
AU - Negreiros, R.
AU - Alves, A.
AU - Valadares, D.
AU - Perkusich, A.
PY - 2022
SP - 93
EP - 100
DO - 10.5220/0011339700003286
PB - SciTePress