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DOI: 10.14569/IJACSA.2021.0120764
PDF

An ICU Admission Predictive Model for COVID-19 Patients in Saudi Arabia

Author 1: Hamza Ghandorh
Author 2: Muhammad Zubair Khan
Author 3: Raed Alsufyani
Author 4: Mehshan Khan
Author 5: Yousef M. Alsofayan
Author 6: Anas A. Khan
Author 7: Ahmed A. Alahmari

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 12 Issue 7, 2021.

  • Abstract and Keywords
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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.

Keywords: Covid-19; ANN; ensemble learning method; predic-tion; ICU admission; Saudi Arabia

Hamza Ghandorh, Muhammad Zubair Khan, Raed Alsufyani, Mehshan Khan, Yousef M. Alsofayan, Anas A. Khan and Ahmed A. Alahmari, “An ICU Admission Predictive Model for COVID-19 Patients in Saudi Arabia” International Journal of Advanced Computer Science and Applications(IJACSA), 12(7), 2021. http://dx.doi.org/10.14569/IJACSA.2021.0120764

@article{Ghandorh2021,
title = {An ICU Admission Predictive Model for COVID-19 Patients in Saudi Arabia},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2021.0120764},
url = {http://dx.doi.org/10.14569/IJACSA.2021.0120764},
year = {2021},
publisher = {The Science and Information Organization},
volume = {12},
number = {7},
author = {Hamza Ghandorh and Muhammad Zubair Khan and Raed Alsufyani and Mehshan Khan and Yousef M. Alsofayan and Anas A. Khan and Ahmed A. Alahmari}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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