Respiratory failure in COVID-19 patients a comparative study of smokers to nonsmokers - Mohammad Kharabsheh; Shadi Banitaan; Hakam W. Alomari; Mohammad Alshirah; Sukaina Alzyoud (Indonesian Journal of Electrical Engineering and Computer Science, 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.