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.
Classification CNN and COVID-19; CXR images; Deep Learning; Computer aided diagnosis; Image classification; Medical imaging; Polymerase chain reaction; Viruses; Chest X-ray image; Classification models; Computer aided diagnostics; Diagnostic methods; Imaging assays; PCR assay; Training network; Upper layer; COVID-19
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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