Deep Learning Tools for Covid-19 Pneumonia Classification

The outbreak of Covid-19 has triggered a worldwide problem, especially in Asia and America. The World Health Organization (WHO) declared the sickness a pandemic on March 20, 2020. It arrived in waves, and most countries worldwide have now experienced two waves and are on the approach of experiencing the third. The goal of this study is to build up and certify a Computer-Aided Diagnosis (CADx) system for distinguishing between COVID-19-positive patients and non-COVID Patients people. Chest X-ray (CXR) images will be used to accomplish this. From public datasets which we got on GitHub 2295 CXR images were obtained which included 712 COVID-19 positive and 1583 normal. The proposed CADx system utilized a Conventional Neural Network (CNN) model for data argumentation and CNN was built, compiled, and trained with the help of TensorFlow and Keras. For the sake of appraisal, our datasets were separated into three categories: Train/Test and Validation. The three sets’ accuracy was evaluated and the results for Training, Validation, and Test were 97.77%, 97.81%, and 97.72% respectively. In the end, this study was able to create a precise Computer-Aided Diagnosis system for the two categories of classification.