Extracting Insights and Prognosis of Corona Disease

Rao, V. C. S.; Gampa, S.; Rama, V.; Anumala, H.; Gadepally, A.

COVID-19, Corona Virus Disease-2019, belongs to the genus of Coronaviridae. A pandemic with no immunogen or has neither clinically well-Tried immunogen nor medicine making unpredictable havocs within the human lives in each country throughout the globe. In this paper, we put forward a web app that enables users to predict covid19 results in real time using an online intelligent device. This app is jam-packed with information that allows the user to describe their COVID symptoms. It then processes user-specific details to see whether a person is affected with covid19. This entire process is done using an intelligent data mining technique to develop data mining prediction models which are further used for the guessing of COVID-19, with an epidemiological data of COVID-19 patients of South Korea. An analysis of datasets is done to understand how a person is affected. These Prediction models are built using machine learning algorithms like decision tree (DT), logistic regression (LR), random forest (RF), and K-nearest neighbor (KNN) and their performances are computed and evaluated. These algorithms were directly applied to the data with python as programming language to develop the different models. The output of this study have proven that the model developed with a Random forest DM algorithm stands to be the best model to predict the infected patients more effectively among the models developed with different algorithms, with an overall accuracy of 98.83% © 2021 IEEE.