Esraa Mugdadi, Ismail Hmeidi, Ahmad Al-Aiad, Naser Obeidat
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Deep learning approach for classifying CT images of COVID-19: A Systematic Review
COVID-19 is the most disease that millions of people around the world suffer from it. This disease appears at the end of the year of 2019 to today. The first case appeared from China. The World Health organization (WHO) called it the pandemic as WHO the total cases infected with COVID-19. This paper on a systematic study of the literature on the study of the model of deep learning to classify the CT images of COVID-19 which was published from the start of this pandemic. We study the 38 research which related to our object. we provided research of classification that summarizes the CT images, the nine deep learning algorithms used. We identified the main gaps in the previous study which not been solved, and suggestions solve for future research.
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