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Developing an efficient deep neural network for automatic detection of COVID-19 using chest X-ray images

The novel coronavirus (COVID-19) could be described as the greatest human challenge of the 21st century. The development and transmission of the disease have increased mortality in all countries. Therefore, a rapid diagnosis of COVID-19 is necessary to treat and control the disease. In this paper, a...

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Bibliographic Details
Main Authors: Sobhan Sheykhivand, Zohreh Mousavi, Sina Mojtahedi, Tohid Yousefi Rezaii, Ali Farzamnia, Saeed Meshgini, Ismail Saad
Format: Article
Language:English
English
Published: Elsevier BV 2021
Subjects:
R Medicine (General)
Online Access:https://eprints.ums.edu.my/id/eprint/26764/1/Developing%20an%20efficient%20deep%20neural%20network%20for%20automatic%20detection%20of%20COVID-19%20using%20chest%20X-ray%20images.pdf
https://eprints.ums.edu.my/id/eprint/26764/2/Developing%20an%20efficient%20deep%20neural%20network%20for%20automatic%20detection%20of%20COVID-19%20using%20chest%20X-ray%20images.pdf
https://eprints.ums.edu.my/id/eprint/26764/
https://doi.org/10.1016/j.aej.2021.01.011
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https://eprints.ums.edu.my/id/eprint/26764/1/Developing%20an%20efficient%20deep%20neural%20network%20for%20automatic%20detection%20of%20COVID-19%20using%20chest%20X-ray%20images.pdf
https://eprints.ums.edu.my/id/eprint/26764/2/Developing%20an%20efficient%20deep%20neural%20network%20for%20automatic%20detection%20of%20COVID-19%20using%20chest%20X-ray%20images.pdf
https://eprints.ums.edu.my/id/eprint/26764/
https://doi.org/10.1016/j.aej.2021.01.011

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