Abstract
Globally, COVID-19 already emerged in around 170 million confirmed cases of infected people and, as of May 31, 2021, affected more than 3.54 million deaths. This pandemic has given rise to numerous public health and socioeconomic issues, emphasizing the significance of unraveling the epidemic’s history and forecasting the disease’s potential dynamics. A variety of mathematical models have been proposed to obtain a deeper understanding of disease transmission mechanisms. Machine Learning (ML) models have been used in the last decade to identify patterns and enhance prediction efficiency in healthcare applications. This paper proposes a model to predict COVID-19 patients admission to the intensive care unit (ICU). The model is built upon robust known classification algorithms, including classic Machine Learning Classifiers (MLCs), an Artificial Neural Network (ANN) and ensemble learning. This model’s strength in predicting COVID-19 infected patients is shown by performance analysis of various MLCs and error metrics. Among other used ML models, the ANN model resulted in the highest accuracy, 97.9% over other models. Mean Squared Error showed that the ANN method had the lowest error (0.0809). In conclusion, this paper could be beneficial to ICU staff to predict ICU admission based on COVID-19 patients’ clinical characteristics.
Highlights
The 2019 coronavirus disease (COVID-19) emerged as a global public health emergency on December 12, 2020, affecting 220 countries worldwide
The findings show that followed by linear regression (LR) and LASSO; the exponential smoothing (ES) performed best out of all the models used, which performs well in predicting newly recorded incidents, death rate, and recovery rate, while support vector machine (SVM) performs poorly in all projection scenarios given the available dataset
The proposed model provided 97.93% accuracy, while the comparative models attained an average accuracy of 87.28%, so that the proposed model showed a 10.7% performance gain
Summary
The 2019 coronavirus disease (COVID-19) emerged as a global public health emergency on December 12, 2020, affecting 220 countries worldwide This disease is caused by an extreme acute respiratory syndrome called coronavirus 2 (SARS-CoV-2) [1, 2], first identified in Wuhan, China. This new virus began to transmit rapidly globally, and the WHO declared the epidemic to be International Public Health Emergency of International Concern (PHEIC), and soon after it was declared a pandemic [3, 4]. Around 170 million confirmed cases and more than 3.54 million deaths were registered worldwide, with a Case Fatality Rate (CFR) of 2 as of May 31, 2020, [5]. In the same time interval, the Kingdom of Saudi Arabia has registered a lower CFR 1.7 similar to the international clinical manifestation and risk factors of COVID19 [6, 7, 8].
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