Classifying COVID-19 positive X-ray using deep learning models



COVID-19, x-ray image, pneumonia, Deep Learning, binary classification, multiclass classification


COVID-19 is a pandemic characterized by uncertainty not only in transmission and pathogenicity, but also in disease-specific control options. Despite many governmental measures, the disease is spreading and in many countries, the public health system is close to be collapsed. Alternative techniques should be taken in order to minimize the COVID-19 negative impacts on the society. This work presents preliminary results of deep learning models to classify COVID-19 positive based on X-ray images. We provide binary classification (COVID-19 vs healhty, and COVID-19 vs pneumonia) and also multiclass (COVID-19 vs pneumonia vs healhty). Results show that VGG models present the best results, achiving 98.81% of precision in binary classification, and 91.68% in multiclass classification.





Special Issue on Fighting against COVID-19
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