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All Journal Green Intelligent Systems and Applications
Yew Fai Cheah
Faculty of Engineering and Science, Curtin University, Malaysia
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Chest X-Ray Classification of Lung Diseases Using Deep Learning Yew Fai Cheah
Green Intelligent Systems and Applications Vol. 1 Iss. 1 (2021)
Publisher : Tecno Scientifica Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (318.61 KB) | DOI: 10.53623/gisa.v1i1.32

Abstract

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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