Detection of Recovery of Covid-19 Cases using Machine Learning

Introduction: Classification is one of the most important research and applications of machine learning techniques Research in the area of human-machine interaction and machine learning contributed to the success of Chatbots Objective: This research concentrates on some of the most important developments in machine learning classification research and the issues of Coronavirus Disease 2019 (COVID-19) Since December 2019, COVID-19 has been causing a massive health crisis all over the world resulted in 5,418,237 confirmed and 344,201 death COVID-19 cases to date (24 05 2020) Clinical experts say that COVID-19 patients to be diagnosed in early-stage to save their lives Methods: This study attempted to detect COVID-19 patients who can recover from the disease, using machine learning techniques, so that suitable treatment can be given to the patients to save their lives Support Vector Machines (SVM), Artificial Neural Network (ANN), Decision tree, K-Nearest Neighbors (KNN), Random Forest and Logistic Regression algorithms are used to evaluate the classification performance Result and Conclusion: In this paper, a Chatbot was developed using the best algorithm evaluated to serve the society suffering from COVID-19 © IJCRR