ACCURACY OF NEURAL NETWORK MODEL IN PREDICTING OUTCOME OF COVID 19 USING DEEP LEARNING APPROACH

Abstract

COVID-19 as the disease of concern motivates various scientists to investigate it in various perspectives. In statistical perspective, a number of statistical models are used to predict the outcome of COVID-19 cases given a number of risk factors. Accuracy of a statistical model in predicting the outcome is important to be determined. A part of supervised machine learning called deep learning is used to predict the outcome of COVID-19 given five predictors, new cases, age >= 65 years, prevalence of diabetes mellitus, female smoker, and male smoker. Big data of COVID-19 is downloaded from the website. A thousand data sets have been analyzed by neural network algorithm using library Keras.