WEB Predictor COVIDz: Deep Learning for COVID-19 Disease Detection from chest X-rays

摘要

While writing these words, the number of COVID-19 infected persons exceeded 20 730 456 and caused 751 154 deaths across the world as reported by WHO (World Health Organization) statistics [1]. The matter has become a reality and the damage is very severe, there is no longer any way to save humanity from this epidemic except diagnose and prevention, especially with the delay in the emergence of any vaccine recognized by the World Health Organization so far. Without therapeutic treatment or explicit restorative immunizations for COVID-19, it is fundamental to distinguish the malady at a beginning phase and to have the option to quickly seclude a contaminated patient. This study, therefore, looked at the diagnostic value and consistency of chest imaging. Access to imaging is not always possible, accessible, or feasible. Our application solves this problem and from a WEB Predictor COVIDz and a program with deep learning we will be able to systematically bring the chest X-ray image and predict the percentage of absence or presence of COVID-19. The proposed approach (Custom VGG model) and our WEB site COVIDz objective validation of the suggested solution obtained the best classification efficiency 99,64%, F -score of 99,2%, Precision of 99,28%, MCC of 99,28%, recall of 99,28%, and a Specificity value of 100%.