A Novel Approach for Predicting COVID-19 Using Machine Learning-Based Logistic Regression Classification MODEL

Abstract

Recently, several studies have stated that mild weather can perhaps halt the global epidemic, which has already afflicted over 1.6 million people globally. Clarification of such correlations in the worst affected country, the US, can be extremely valuable to understand the function of weather in transmission of the disease in the highly populated countries, such as India. The authors developed a machine-learning approach as logistic regression classification models that used data from several sources to determine whether a patient is at risk of COVID-19 using one of the classification models with the greatest accuracy. They are working on a model that uses simple features available through basic clinical inquiries to detect COVID-19 patients. When testing resources are tight, their approach can be used to prioritize testing for COVID-19, among other things.