Journal ArticleOpen Access
Transfer learning with fine-tuned deep CNN ResNet50 model for classifying COVID-19 from chest X-ray images
Authors
Author Affiliations
Pabna University of Science and Technology, Uttara University, Dhaka University of Engineering & Technology, Chittagong University of Engineering & Technology
Published InInformatics in Medicine Unlocked
Year2022
Citations153
Abstract
COVID-19 cases are putting pressure on healthcare systems all around the world. Due to the lack of available testing kits, it is impractical for screening every patient with a respiratory ailment using traditional methods (RT-PCR). In addition, the tests have a high turn-around time and low sensitivity. Detecting suspected COVID-19 infections from the chest X-ray might help isolate high-risk people before the RT-PCR test. Most healthcare systems already have X-ray equipment, and because most current X-ray systems have already been computerized, there is no need to transfer the samples. The use of a chest X-ray to prioritize the selection of patients for subsequent RT-PCR testing is the motivation of this work. Transfer learning (TL) with fine-tuning on deep convolutional neural…
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