X-Ray Equipped with Artificial Intelligence: Changing the COVID-19 Diagnostic Paradigm during the Pandemic

Purpose. Due to the excessive use of raw materials in diagnostic tools and equipment during the COVID-19 pandemic, there is a dire need for cheaper and more effective methods in the healthcare system. With the development of artificial intelligence (AI) methods in medical sciences as low-cost and sa...

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Main Authors: Mustafa Ghaderzadeh, Mehrad Aria, Farkhondeh Asadi
Format: Article
Language:English
Published: Hindawi Limited 2021-01-01
Series:BioMed Research International
Online Access:http://dx.doi.org/10.1155/2021/9942873
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spelling doaj-5da9f8ca07424342a572aaf608770ea42021-09-06T00:00:22ZengHindawi LimitedBioMed Research International2314-61412021-01-01202110.1155/2021/9942873X-Ray Equipped with Artificial Intelligence: Changing the COVID-19 Diagnostic Paradigm during the PandemicMustafa Ghaderzadeh0Mehrad Aria1Farkhondeh Asadi2Student Research CommitteeDepartment of Computer EngineeringDepartment of Health Information Technology and ManagementPurpose. Due to the excessive use of raw materials in diagnostic tools and equipment during the COVID-19 pandemic, there is a dire need for cheaper and more effective methods in the healthcare system. With the development of artificial intelligence (AI) methods in medical sciences as low-cost and safer diagnostic methods, researchers have turned their attention to the use of imaging tools with AI that have fewer complications for patients and reduce the consumption of healthcare resources. Despite its limitations, X-ray is suggested as the first-line diagnostic modality for detecting and screening COVID-19 cases. Method. This systematic review assessed the current state of AI applications and the performance of algorithms in X-ray image analysis. The search strategy yielded 322 results from four databases and google scholar, 60 of which met the inclusion criteria. The performance statistics included the area under the receiver operating characteristics (AUC) curve, accuracy, sensitivity, and specificity. Result. The average sensitivity and specificity of CXR equipped with AI algorithms for COVID-19 diagnosis were >96% (83%-100%) and 92% (80%-100%), respectively. For common X-ray methods in COVID-19 detection, these values were 0.56 (95% CI 0.51-0.60) and 0.60 (95% CI 0.54-0.65), respectively. AI has substantially improved the diagnostic performance of X-rays in COVID-19. Conclusion. X-rays equipped with AI can serve as a tool to screen the cases requiring CT scans. The use of this tool does not waste time or impose extra costs, has minimal complications, and can thus decrease or remove unnecessary CT slices and other healthcare resources.http://dx.doi.org/10.1155/2021/9942873
collection DOAJ
language English
format Article
sources DOAJ
author Mustafa Ghaderzadeh
Mehrad Aria
Farkhondeh Asadi
spellingShingle Mustafa Ghaderzadeh
Mehrad Aria
Farkhondeh Asadi
X-Ray Equipped with Artificial Intelligence: Changing the COVID-19 Diagnostic Paradigm during the Pandemic
BioMed Research International
author_facet Mustafa Ghaderzadeh
Mehrad Aria
Farkhondeh Asadi
author_sort Mustafa Ghaderzadeh
title X-Ray Equipped with Artificial Intelligence: Changing the COVID-19 Diagnostic Paradigm during the Pandemic
title_short X-Ray Equipped with Artificial Intelligence: Changing the COVID-19 Diagnostic Paradigm during the Pandemic
title_full X-Ray Equipped with Artificial Intelligence: Changing the COVID-19 Diagnostic Paradigm during the Pandemic
title_fullStr X-Ray Equipped with Artificial Intelligence: Changing the COVID-19 Diagnostic Paradigm during the Pandemic
title_full_unstemmed X-Ray Equipped with Artificial Intelligence: Changing the COVID-19 Diagnostic Paradigm during the Pandemic
title_sort x-ray equipped with artificial intelligence: changing the covid-19 diagnostic paradigm during the pandemic
publisher Hindawi Limited
series BioMed Research International
issn 2314-6141
publishDate 2021-01-01
description Purpose. Due to the excessive use of raw materials in diagnostic tools and equipment during the COVID-19 pandemic, there is a dire need for cheaper and more effective methods in the healthcare system. With the development of artificial intelligence (AI) methods in medical sciences as low-cost and safer diagnostic methods, researchers have turned their attention to the use of imaging tools with AI that have fewer complications for patients and reduce the consumption of healthcare resources. Despite its limitations, X-ray is suggested as the first-line diagnostic modality for detecting and screening COVID-19 cases. Method. This systematic review assessed the current state of AI applications and the performance of algorithms in X-ray image analysis. The search strategy yielded 322 results from four databases and google scholar, 60 of which met the inclusion criteria. The performance statistics included the area under the receiver operating characteristics (AUC) curve, accuracy, sensitivity, and specificity. Result. The average sensitivity and specificity of CXR equipped with AI algorithms for COVID-19 diagnosis were >96% (83%-100%) and 92% (80%-100%), respectively. For common X-ray methods in COVID-19 detection, these values were 0.56 (95% CI 0.51-0.60) and 0.60 (95% CI 0.54-0.65), respectively. AI has substantially improved the diagnostic performance of X-rays in COVID-19. Conclusion. X-rays equipped with AI can serve as a tool to screen the cases requiring CT scans. The use of this tool does not waste time or impose extra costs, has minimal complications, and can thus decrease or remove unnecessary CT slices and other healthcare resources.
url http://dx.doi.org/10.1155/2021/9942873
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