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Covid-19 pandemic caused by the SARS-CoV-2 has claimed numerous lives around the world. We developed a novel predictive model based on machine learning algorithms to predict the mortality risk of patients with COVID-19. In this study, we used documented data of 117,000 patients worldwide with laboratory-confirmed COVID-19. This study proposes a predictive model to help hospitals and medical facilities decide who has higher priority to be hospitalized and triage patients when the system is overwhelmed by overcrowding. The results demonstrate 93% overall accuracy in predicting the mortality rate. We used a number of machine learning algorithms including artificial neural networks, support vector machine (SVM), and random forest to predict the mortality rate in patients with COVID-19. In this study, the most alarming symptoms and features were also identified. |
