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Coronavirus is a large virus family consisting of diverse viruses, some ofwhich disseminate among mammals and others cause sickness among humans.COVID-19 is highly contagious and is rapidly spreading, rendering its earlydiagnosis of preeminent status. Researchers, medical specialists andorganizations all over the globe have been working tirelessly to combat thisvirus and help in its containment. In this paper, a novel neural network calledWisdomNet has been proposed, for the diagnosis of COVID-19 using chest X-rays.The WisdomNet uses the concept of Wisdom of Crowds as its founding idea. It isa two-layered convolutional Neural Network (CNN), which takes chest x-rayimages as input. Both layers of the proposed neural network consist of a numberof neural networks each. The dataset used for this study consists of chestx-ray images of COVID-19 positive patients, compiled and shared by Dr. Cohen onGitHub, and the chest x-ray images of healthy lungs and lungs affected by viraland bacterial pneumonia were obtained from Kaggle. The network not onlypinpoints the presence of COVID-19, but also gives the probability of thedisease maturing into Acute Respiratory Distress Syndrome (ARDS). Thus,predicting the progression of the disease in the COVID-19 positive patients.The network also slender the occurrences of false negative cases by employing ahigh threshold value, thus aids in curbing the spread of the disease and givesan accuracy of 100% for successfully predicting COVID-19 among the chest x-raysof patients affected with COVID-19, bacterial and viral pneumonia.

journal of pure and applied microbiology

WisdomNet: Prognosis of COVID-19 with Slender Prospect of False Negative  Cases and Vaticinating the Probability of Maturation to ARDS using  Posteroanterior Chest X-Rays