Explainable DCNN based chest X-ray image analysis and classification for COVID-19 pneumonia detection

Abstract To speed up the discovery of COVID-19 disease mechanisms by X-ray images, this research developed a new diagnosis platform using a deep convolutional neural network (DCNN) that is able to assist radiologists with diagnosis by distinguishing COVID-19 pneumonia from non-COVID-19 pneumonia in...

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Autores principales:	Jie Hou, Terry Gao
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/545602688df14dda9eb1eb3571c562bd
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spelling	oai:doaj.org-article:545602688df14dda9eb1eb3571c562bd2021-12-02T16:27:50ZExplainable DCNN based chest X-ray image analysis and classification for COVID-19 pneumonia detection10.1038/s41598-021-95680-62045-2322https://doaj.org/article/545602688df14dda9eb1eb3571c562bd2021-08-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-95680-6https://doaj.org/toc/2045-2322Abstract To speed up the discovery of COVID-19 disease mechanisms by X-ray images, this research developed a new diagnosis platform using a deep convolutional neural network (DCNN) that is able to assist radiologists with diagnosis by distinguishing COVID-19 pneumonia from non-COVID-19 pneumonia in patients based on chest X-ray classification and analysis. Such a tool can save time in interpreting chest X-rays and increase the accuracy and thereby enhance our medical capacity for the detection and diagnosis of COVID-19. The explainable method is also used in the DCNN to select instances of the X-ray dataset images to explain the behavior of training-learning models to achieve higher prediction accuracy. The average accuracy of our method is above 96%, which can replace manual reading and has the potential to be applied to large-scale rapid screening of COVID-9 for widely use cases.Jie HouTerry GaoNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-15 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Jie Hou Terry Gao Explainable DCNN based chest X-ray image analysis and classification for COVID-19 pneumonia detection
description	Abstract To speed up the discovery of COVID-19 disease mechanisms by X-ray images, this research developed a new diagnosis platform using a deep convolutional neural network (DCNN) that is able to assist radiologists with diagnosis by distinguishing COVID-19 pneumonia from non-COVID-19 pneumonia in patients based on chest X-ray classification and analysis. Such a tool can save time in interpreting chest X-rays and increase the accuracy and thereby enhance our medical capacity for the detection and diagnosis of COVID-19. The explainable method is also used in the DCNN to select instances of the X-ray dataset images to explain the behavior of training-learning models to achieve higher prediction accuracy. The average accuracy of our method is above 96%, which can replace manual reading and has the potential to be applied to large-scale rapid screening of COVID-9 for widely use cases.
format	article
author	Jie Hou Terry Gao
author_facet	Jie Hou Terry Gao
author_sort	Jie Hou
title	Explainable DCNN based chest X-ray image analysis and classification for COVID-19 pneumonia detection
title_short	Explainable DCNN based chest X-ray image analysis and classification for COVID-19 pneumonia detection
title_full	Explainable DCNN based chest X-ray image analysis and classification for COVID-19 pneumonia detection
title_fullStr	Explainable DCNN based chest X-ray image analysis and classification for COVID-19 pneumonia detection
title_full_unstemmed	Explainable DCNN based chest X-ray image analysis and classification for COVID-19 pneumonia detection
title_sort	explainable dcnn based chest x-ray image analysis and classification for covid-19 pneumonia detection
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/545602688df14dda9eb1eb3571c562bd
work_keys_str_mv	AT jiehou explainabledcnnbasedchestxrayimageanalysisandclassificationforcovid19pneumoniadetection AT terrygao explainabledcnnbasedchestxrayimageanalysisandclassificationforcovid19pneumoniadetection
_version_	1718383990831841280

Explainable DCNN based chest X-ray image analysis and classification for COVID-19 pneumonia detection

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