A machine learning approach to predict critical illness in Covid-19 patients

The unprecedented COVID-19 epidemic wreaked havoc on world economy as well as on entire healthcare system. Medical professionals experienced a tough time in detecting and treating this pandemic due to a lack of expertise. It is quiet imperative to deal with the current circumstances in order to live healthier lives in the future. In this article logistic regression along with principal component analysis is carried out on the data acquired from Mexican government’s official website of patients suffering from COVID-19 in order to predict the serious effects of the disease. The proposed methodology is evaluated using several evaluation metrics such as accuracy, precision and recall those having values 0.86, 0.65, 0.46 respectively.