ConvCoroNet: a deep convolutional neural network optimized with iterative thresholding algorithm for Covid-19 detection using chest X-ray images

Covid-19 is a global pandemic. Early and accurate detection of positive cases prevent the further spread of this epidemic and help to treat rapidly the infected patients. During the peak of this epidemic, there was an insufficiency of Covid-19 test kits. In addition, this technique takes a considera...

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Veröffentlicht in:	Journal of biomolecular structure & dynamics Jg. 42; H. 11; S. 5699 - 5712
Hauptverfasser:	Merrouchi, M., Benyoussef, Y., Skittou, M., Atifi, K., Gadi, T.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	England Taylor & Francis 23.07.2024
Schlagworte:	Algorithms ConvCoroNet convolutional neural network (CNNs) covid-19 COVID-19 - diagnosis COVID-19 - diagnostic imaging COVID-19 - virology deep learning Humans iterative thresholding algorithm based optimizer Neural Networks, Computer Radiography, Thoracic - methods SARS-CoV-2 Sensitivity and Specificity support vector machine (SVM) X-ray chest images convolutional neural network (CNNs) deep learning iterative thresholding algorithm based optimizer support vector machine (SVM) covid-19 ConvCoroNet X-ray chest images
ISSN:	0739-1102, 1538-0254, 1538-0254
Online-Zugang:	Volltext
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