COVID-19 Détection using Deep Learning Based Approaches

Abstract

Currently, the detection of coronavirus disease (COVID-19) is one of the main challenges in the world, given the rapid spread of the disease. Recent statistics indicate that the number of people diagnosed with COVID-19 is increasing exponentially, with more than 1.6 million confirmed cases; the disease is spreading to many countries across the world. The objective of this work is to propose a Deep Learning approach in the field of epidemiology to detect coronavirus. To do this, we have chosen to use the Convolutional Neural networks (CNN), where different models have been implemented allowing us to obtain the best results. In this study, we proposed three Convolutional Neural Network approaches and crated three models based on these approaches, the created models were trained and prove their efficiency by achieving high accuracy and F1-Score in their testing using real-world chest CT scans dataset