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COVID-19 vs influenza viruses: A cockroach optimized deep neural network classification approach #MMPMID33821096
El-Dosuky MA; Soliman M; Hassanien AE
Int J Imaging Syst Technol 2021[Jun]; 31 (2): 472-482 PMID33821096show ga
Among Coronavirus, as with many other viruses, receptor interactions are an essential determinant of species specificity, virulence, and pathogenesis. The pathogenesis of the COVID-19 depends on the virus's ability to attach to and enter into a suitable human host cell. This paper presents a cockroach optimized deep neural network to detect COVID-19 and differentiate between COVID-19 and influenza types A, B, and C. The deep network architecture is inspired using a cockroach optimization algorithm to optimize the deep neural network hyper-parameters. COVID-19 sequences are obtained from repository 2019 Novel Coronavirus Resource, and influenza A, B, and C sub-dataset are obtained from other repositories. Five hundred ninety-four unique genomes sequences are used in the training and testing process with 99% overall accuracy for the classification model.