COVID-19 prediction using AI deep VGG16 model from X-ray images Online publication date: Mon, 31-Jul-2023
by Narenthirakumar Appavu; C. Nelsonkennedybabu
International Journal of Bioinformatics Research and Applications (IJBRA), Vol. 19, No. 2, 2023
Abstract: Using human lung X-rays, an advanced technique is currently being used to diagnose COVID-19. Many deep learning concepts piece an imperative role in detecting COVID-19. In this proposed thesis, we presented VGG16 deep learning model for COVID-19 in a precise and timely way. The proposed model used a two-way classification system to differentiate the lung X-rays according to the given input. Finally, it detects affected and normal lung X-rays. The effectiveness of the proposed system is gaged by evaluation criteria as in accuracy, precision, recall and F1 score. More than 2,000 samples were used to diagnose COVID-19. The VGG16 model gives the best results of 99.58% COVID-19 recognition performance for the provided sample size's two-class categorisation. It is superior compared to all existing approaches in the literature. Medical professionals and healthcare workers can use the proposed system to accurately identify COVID-19 using X-rays of human lungs.
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