This approach demonstrates effective covid-19 recognition using deep learning and feature selection, suggesting improved diagnostic processes.
COVID-19 has become a great challenge to the whole world, as it has infected and killed millions of people and affected the different fields of our life due to its rapid ability to spread. In this paper, the COVID-19 patient's recognition technique utilized the deep learning, and An artificial bee colony is intended to be applied. Deep learning was implemented to provides the features from X-ray images, while the artificial bee colony algorithm used to refine these features by selecting the best features. The multilayer perceptron classifier has been utilized in the classification stage. The experiments carried out on the standard dataset with/without different other daises such as MERS, SARS, and ARDS as well as COVID-19(+) referred that the proposed work provided high recognition rates with high reduction in the number of deep learning features.
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Sahan et al. (2021) studied this question.
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