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Article | Green Intelligent Systems and Applications | Volume 1 - Issue 1 - 2021 | 12-18 | https://doi.org/10.53623/gisa.v1i1.32
© 2021 by the author(s), and is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) License Creative Commons Attribution 4.0 International (CC BY 4.0) License

Chest X-Ray Classification of Lung Diseases Using Deep Learning

Author(s): Yew Fai Cheah
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Faculty of Engineering and Science, Curtin University, Malaysia

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Green Intelligent Systems and Applications

Volume 1 - Issue 1 - 2021

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Chest X-ray images can be used to detect lung diseases such as COVID-19, viral pneumonia, and tuberculosis (TB). These diseases have similar patterns and diagnoses, making it difficult for clinicians and radiologists to differentiate between them. This paper uses convolutional neural networks (CNNs) to diagnose lung disease using chest X-ray images obtained from online sources. The classification task is separated into three and four classes, with COVID-19, normal, TB, and viral pneumonia, while the three-class problem excludes the normal lung. During testing, AlexNet and ResNet-18 gave promising results, scoring more than 95% accuracy.
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SUBMITTED: 06 October 2021
ACCEPTED: 19 October 2021
PUBLISHED: 29 November 2021
SUBMITTED to ACCEPTED: 13 days
DOI: https://doi.org/10.53623/gisa.v1i1.32

Cite this article
Cheah, Y. F. (2021). Chest X-Ray Classification of Lung Diseases Using Deep Learning. Green Intelligent Systems and Applications, 1(1), 12–18. https://doi.org/10.53623/gisa.v1i1.32
Keywords
CNN COVID-19 tuberculosis viral pneumonia
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