Hospitalization Priority of COVID-19 Patients using Machine Learning

With each new wave of COVID-19, the number of patients requiring hospital beds increases, and as we have observed from our previous experiences, a lot of people have lost lives because of the unavailability of hospital beds at the right time. Hence this paper aims to resolve such a situation by the prioritization of patients using machine learning algorithms. Prioritization of patients at a hospital is the process of ordering or ranking patients based on various factors, to make a fair decision about which patient is in utmost need of care. This paper studies the different algorithms like Decision Tree Classifier, Naive Bayes and KNeighbors Classifier with which such a system could be made to predict the severity of patients and finally proposes a fair and efficient system to rank COVID-19 patients based on their severity.