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Classifying Chest X-rays for COVID-19 using Deep Learning
2023 IEEE International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, ICIITCEE 2023 ; : 1084-1089, 2023.
Article in English | Scopus | ID: covidwho-2319509
ABSTRACT
A developing virus called COVID-19 infects the lungs and upper layer respiratory system. Medical imaging and PCR assays can be used to identify COVID-19. Medical images are used to identify COVID-19 diseases in the proposed classification model, which works well. A crucial step in the battle against this fatal illness may turn out to be an efficient screening and diagnostic phase in treating infected sufferers. Chest X-ray (CXR) scans could be used to do this. The utilization of chest X-ray imaging for early detection may prove to be a crucial strategy in the fight against COVID-19. Many computer- aided diagnostic (CAD) methods have been developed to help radiologists and provide them with more information for the same. In a training network with many classes, tertiary classification starts to become more accurate as the number of classes increases. © 2023 IEEE.
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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 2023 IEEE International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, ICIITCEE 2023 Year: 2023 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 2023 IEEE International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, ICIITCEE 2023 Year: 2023 Document Type: Article