A modified CNN-based Covid-19 detection using CXR

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Mohammad Hossein Amini*
Mohammad Bagher Menhaj
Heidar Ali Talebi

Abstract



In this paper, a deep neural network for the purpose of detecting COVID-19 from Chest X-Ray (CXR) images is presented. Since this pandemic has emerged worldwide , there is no large dataset available for it. So for its detection, care must be taken not to use methods with high variance. However, for a deep neural network to get acceptable performance, we usually need huge amounts of datasets. Otherwise, there may be issues like overfitting. To resolve this problem, we use the beautiful idea of transfer learning. Training a deep neural network with the idea of transfer learning on 2 available datasets on the web, we achieved a COVID-19 detection accuracy of 98% on about 1000 test samples.


1(Use footnote for providing further information about author (webpage, alternative address)—not for acknowledging funding agencies.)



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Article Details

Amini, M. H., Menhaj, M. B., & Talebi, H. A. (2021). A modified CNN-based Covid-19 detection using CXR. Archives of Community Medicine and Public Health, 7(2), 142–145. https://doi.org/10.17352/2455-5479.000154
Research Articles

Copyright (c) 2021 Amini MH, et al.

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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Cohen JP, Morrison P, Dao L (2020) COVID-19 image data collection. arXiv 2003.11597. Link: https://bit.ly/3eIFT6L

Praveen (2020) CoronaHack Chest X-Ray-Dataset. Kaggle. Link: https://bit.ly/3eNc7NY