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DETECTION OF COVID-19 FROM RADIOGRAPHS

COVID-19 pandemic has caused millions of deaths in more than 150 countries around the
world. Detecting this disease from radiography and radiology images is perhaps one of the fastest ways
to diagnose the patients. This application can be used by anyone to detect whether a person is COVID-19
affected or not according to his/her chest x-ray. The process of detecting whether a person is COVID-19
affected or not can be automated by training a deep learning model so that it can predict the given x-ray
accurately. This is a Supervised learning problem and classification algorithms are used. The dataset used
is collected from GitHub (Covid-19 positive x-rays) and Kaggle (Covid-19 negative x-rays). CNNs are
extensively used and combined with consolidated machine learning methods, such as k-Nearest Neighbor,
Bayes, Random Forest, multilayer perceptron (MLP), and support vector machine (SVM). The results will
show if the person is COVID affected by examining his chest x-ray. For working on this project, we have
used python in Jupiter notebook.