COVID-Classifier: an automated machine learning model to assist in the diagnosis of COVID-19 infection in chest X-ray images

Abstract Chest-X ray (CXR) radiography can be used as a first-line triage process for non-COVID-19 patients with pneumonia. However, the similarity between features of CXR images of COVID-19 and pneumonia caused by other infections makes the differential diagnosis by radiologists challenging. We hyp...

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Autores principales:	Abolfazl Zargari Khuzani, Morteza Heidari, S. Ali Shariati
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/8f5178986e1c44ad86fb1f2ff3a40e4c
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spelling	oai:doaj.org-article:8f5178986e1c44ad86fb1f2ff3a40e4c2021-12-02T16:51:03ZCOVID-Classifier: an automated machine learning model to assist in the diagnosis of COVID-19 infection in chest X-ray images10.1038/s41598-021-88807-22045-2322https://doaj.org/article/8f5178986e1c44ad86fb1f2ff3a40e4c2021-05-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-88807-2https://doaj.org/toc/2045-2322Abstract Chest-X ray (CXR) radiography can be used as a first-line triage process for non-COVID-19 patients with pneumonia. However, the similarity between features of CXR images of COVID-19 and pneumonia caused by other infections makes the differential diagnosis by radiologists challenging. We hypothesized that machine learning-based classifiers can reliably distinguish the CXR images of COVID-19 patients from other forms of pneumonia. We used a dimensionality reduction method to generate a set of optimal features of CXR images to build an efficient machine learning classifier that can distinguish COVID-19 cases from non-COVID-19 cases with high accuracy and sensitivity. By using global features of the whole CXR images, we successfully implemented our classifier using a relatively small dataset of CXR images. We propose that our COVID-Classifier can be used in conjunction with other tests for optimal allocation of hospital resources by rapid triage of non-COVID-19 cases.Abolfazl Zargari KhuzaniMorteza HeidariS. Ali ShariatiNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-6 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Abolfazl Zargari Khuzani Morteza Heidari S. Ali Shariati COVID-Classifier: an automated machine learning model to assist in the diagnosis of COVID-19 infection in chest X-ray images
description	Abstract Chest-X ray (CXR) radiography can be used as a first-line triage process for non-COVID-19 patients with pneumonia. However, the similarity between features of CXR images of COVID-19 and pneumonia caused by other infections makes the differential diagnosis by radiologists challenging. We hypothesized that machine learning-based classifiers can reliably distinguish the CXR images of COVID-19 patients from other forms of pneumonia. We used a dimensionality reduction method to generate a set of optimal features of CXR images to build an efficient machine learning classifier that can distinguish COVID-19 cases from non-COVID-19 cases with high accuracy and sensitivity. By using global features of the whole CXR images, we successfully implemented our classifier using a relatively small dataset of CXR images. We propose that our COVID-Classifier can be used in conjunction with other tests for optimal allocation of hospital resources by rapid triage of non-COVID-19 cases.
format	article
author	Abolfazl Zargari Khuzani Morteza Heidari S. Ali Shariati
author_facet	Abolfazl Zargari Khuzani Morteza Heidari S. Ali Shariati
author_sort	Abolfazl Zargari Khuzani
title	COVID-Classifier: an automated machine learning model to assist in the diagnosis of COVID-19 infection in chest X-ray images
title_short	COVID-Classifier: an automated machine learning model to assist in the diagnosis of COVID-19 infection in chest X-ray images
title_full	COVID-Classifier: an automated machine learning model to assist in the diagnosis of COVID-19 infection in chest X-ray images
title_fullStr	COVID-Classifier: an automated machine learning model to assist in the diagnosis of COVID-19 infection in chest X-ray images
title_full_unstemmed	COVID-Classifier: an automated machine learning model to assist in the diagnosis of COVID-19 infection in chest X-ray images
title_sort	covid-classifier: an automated machine learning model to assist in the diagnosis of covid-19 infection in chest x-ray images
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/8f5178986e1c44ad86fb1f2ff3a40e4c
work_keys_str_mv	AT abolfazlzargarikhuzani covidclassifieranautomatedmachinelearningmodeltoassistinthediagnosisofcovid19infectioninchestxrayimages AT mortezaheidari covidclassifieranautomatedmachinelearningmodeltoassistinthediagnosisofcovid19infectioninchestxrayimages AT salishariati covidclassifieranautomatedmachinelearningmodeltoassistinthediagnosisofcovid19infectioninchestxrayimages
_version_	1718382992283402240

COVID-Classifier: an automated machine learning model to assist in the diagnosis of COVID-19 infection in chest X-ray images

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