Respiratory failure in COVID-19 patients a comparative study of smokers to nonsmokers

Mohammad Kharabsheh (The Hashemite University)
Shadi Banitaan (University of Detroit Mercy)
Hakam W. Alomari (Miami University)
Mohammad Alshirah (Al Albayt University)
Sukaina Alzyoud (The Hashemite University)

Indonesian Journal of Electrical Engineering and Computer Science
Vol 27, No 2: August 2022

For many decades, smoking tobacco has been a crucial concern due to respiratory failure. The potential relationship between smoking and COVID-19 has been recently investigated. In this paper, we study and investigate the role of the decision support system to predict the ratio of respiratory failure in smokers versus non-smokers among COVID-19 patients. We employed a classifier that predicts the ratio of respiratory failure as well as the ratio of the death toll between smokers and non-smokers using machine learning methods. The employed model demonstrate a prediction accuracy of 77% when applied on a sample from 23 countries that confirmed the highest number of COVID-19 patients. This was obtained from The World Bank Data-Health Nutrition and Population Statistics. As a result, a strong (significant) relationship between smoking tobacco and COVID-19 was illustrated by the employed model. Our approach achieves a good recall (78%). Thus, smokers are more susceptible to respiratory failure than non-smokers, as COVID-19 complications.