Machine Learning Based Prediction Models for the Percentage Deaths Due to COVID-19

Anwar Jarndal; Saddam Husain; Maha S. Diab; Amir Shikhli

doi:10.1109/DESE54285.2021.9719584

Machine Learning Based Prediction Models for the Percentage Deaths Due to COVID-19

Anwar Jarndal
, Saddam Husain
, Maha S. Diab
, Amir Shikhli

University of Sharjah

University of Sharjah

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

Worldwide COVID-19 pandemic is currently affecting all countries and led to loss of human life. A lot of scientific research are conducted in different areas to improve the future response. The purpose of the project is to use Machine learning (ML) techniques in predicting COVID-19 deaths which will enhance the hospitals response. This paper contributes by developing models that can predict COVID-19 deaths based on three factors: total number of elderly patients (greater than 65 years), diabetic patients, and smoking patients. Gaussian Process Regression (GPR), Support Vector Regression (SVR), Artificial Neural Network-Multi Layer Perceptron (ANN-MLP), and Artificial Neural Network-nonlinear autoregressive network with exogenous inputs (ANN-NARX) approaches are used to build the predictive models. All models are trained and tested using trusted data reported by the World Health Organization (WHO) in various countries. The developed models revealed very good results with excellent prediction rate and performance, especially GPR, which has the best performance. Also, it showed that region-based predictive models are more suitable than a single general model. The GPR predictive model showed the best performance compared to other models.

Original language	English
Title of host publication	2021 14th International Conference on Developments in eSystems Engineering, DeSE 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	418-423
Number of pages	6
ISBN (Electronic)	9781665408882
DOIs	https://doi.org/10.1109/DESE54285.2021.9719584
State	Published - 2021
Event	14th International Conference on Developments in eSystems Engineering, DeSE 2021 - Sharjah, United Arab Emirates Duration: 7 Dec 2021 → 10 Dec 2021

Publication series

Name	Proceedings - International Conference on Developments in eSystems Engineering, DeSE
Volume	2021-December
ISSN (Print)	2161-1343

Conference

Conference	14th International Conference on Developments in eSystems Engineering, DeSE 2021
Country/Territory	United Arab Emirates
City	Sharjah
Period	7/12/21 → 10/12/21

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Artificial neural network
COVID-19
Gaussian process regression
prediction model
support vector regression

Access to Document

10.1109/DESE54285.2021.9719584

Cite this

Jarndal, A., Husain, S., Diab, M. S., & Shikhli, A. (2021). Machine Learning Based Prediction Models for the Percentage Deaths Due to COVID-19. In 2021 14th International Conference on Developments in eSystems Engineering, DeSE 2021 (pp. 418-423). (Proceedings - International Conference on Developments in eSystems Engineering, DeSE; Vol. 2021-December). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/DESE54285.2021.9719584

Jarndal, Anwar ; Husain, Saddam ; Diab, Maha S. et al. / Machine Learning Based Prediction Models for the Percentage Deaths Due to COVID-19. 2021 14th International Conference on Developments in eSystems Engineering, DeSE 2021. Institute of Electrical and Electronics Engineers Inc., 2021. pp. 418-423 (Proceedings - International Conference on Developments in eSystems Engineering, DeSE).

@inproceedings{aabcf7a42df8448cbde341f9efcc21d9,

title = "Machine Learning Based Prediction Models for the Percentage Deaths Due to COVID-19",

abstract = "Worldwide COVID-19 pandemic is currently affecting all countries and led to loss of human life. A lot of scientific research are conducted in different areas to improve the future response. The purpose of the project is to use Machine learning (ML) techniques in predicting COVID-19 deaths which will enhance the hospitals response. This paper contributes by developing models that can predict COVID-19 deaths based on three factors: total number of elderly patients (greater than 65 years), diabetic patients, and smoking patients. Gaussian Process Regression (GPR), Support Vector Regression (SVR), Artificial Neural Network-Multi Layer Perceptron (ANN-MLP), and Artificial Neural Network-nonlinear autoregressive network with exogenous inputs (ANN-NARX) approaches are used to build the predictive models. All models are trained and tested using trusted data reported by the World Health Organization (WHO) in various countries. The developed models revealed very good results with excellent prediction rate and performance, especially GPR, which has the best performance. Also, it showed that region-based predictive models are more suitable than a single general model. The GPR predictive model showed the best performance compared to other models.",

keywords = "Artificial neural network, COVID-19, Gaussian process regression, prediction model, support vector regression",

author = "Anwar Jarndal and Saddam Husain and Diab, \{Maha S.\} and Amir Shikhli",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 14th International Conference on Developments in eSystems Engineering, DeSE 2021 ; Conference date: 07-12-2021 Through 10-12-2021",

year = "2021",

doi = "10.1109/DESE54285.2021.9719584",

language = "English",

series = "Proceedings - International Conference on Developments in eSystems Engineering, DeSE",

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Jarndal, A, Husain, S, Diab, MS & Shikhli, A 2021, Machine Learning Based Prediction Models for the Percentage Deaths Due to COVID-19. in 2021 14th International Conference on Developments in eSystems Engineering, DeSE 2021. Proceedings - International Conference on Developments in eSystems Engineering, DeSE, vol. 2021-December, Institute of Electrical and Electronics Engineers Inc., pp. 418-423, 14th International Conference on Developments in eSystems Engineering, DeSE 2021, Sharjah, United Arab Emirates, 7/12/21. https://doi.org/10.1109/DESE54285.2021.9719584

Machine Learning Based Prediction Models for the Percentage Deaths Due to COVID-19. / Jarndal, Anwar; Husain, Saddam; Diab, Maha S. et al.
2021 14th International Conference on Developments in eSystems Engineering, DeSE 2021. Institute of Electrical and Electronics Engineers Inc., 2021. p. 418-423 (Proceedings - International Conference on Developments in eSystems Engineering, DeSE; Vol. 2021-December).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Machine Learning Based Prediction Models for the Percentage Deaths Due to COVID-19

AU - Jarndal, Anwar

AU - Husain, Saddam

AU - Diab, Maha S.

AU - Shikhli, Amir

PY - 2021

Y1 - 2021

N2 - Worldwide COVID-19 pandemic is currently affecting all countries and led to loss of human life. A lot of scientific research are conducted in different areas to improve the future response. The purpose of the project is to use Machine learning (ML) techniques in predicting COVID-19 deaths which will enhance the hospitals response. This paper contributes by developing models that can predict COVID-19 deaths based on three factors: total number of elderly patients (greater than 65 years), diabetic patients, and smoking patients. Gaussian Process Regression (GPR), Support Vector Regression (SVR), Artificial Neural Network-Multi Layer Perceptron (ANN-MLP), and Artificial Neural Network-nonlinear autoregressive network with exogenous inputs (ANN-NARX) approaches are used to build the predictive models. All models are trained and tested using trusted data reported by the World Health Organization (WHO) in various countries. The developed models revealed very good results with excellent prediction rate and performance, especially GPR, which has the best performance. Also, it showed that region-based predictive models are more suitable than a single general model. The GPR predictive model showed the best performance compared to other models.

AB - Worldwide COVID-19 pandemic is currently affecting all countries and led to loss of human life. A lot of scientific research are conducted in different areas to improve the future response. The purpose of the project is to use Machine learning (ML) techniques in predicting COVID-19 deaths which will enhance the hospitals response. This paper contributes by developing models that can predict COVID-19 deaths based on three factors: total number of elderly patients (greater than 65 years), diabetic patients, and smoking patients. Gaussian Process Regression (GPR), Support Vector Regression (SVR), Artificial Neural Network-Multi Layer Perceptron (ANN-MLP), and Artificial Neural Network-nonlinear autoregressive network with exogenous inputs (ANN-NARX) approaches are used to build the predictive models. All models are trained and tested using trusted data reported by the World Health Organization (WHO) in various countries. The developed models revealed very good results with excellent prediction rate and performance, especially GPR, which has the best performance. Also, it showed that region-based predictive models are more suitable than a single general model. The GPR predictive model showed the best performance compared to other models.

KW - Artificial neural network

KW - COVID-19

KW - Gaussian process regression

KW - prediction model

KW - support vector regression

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M3 - Conference contribution

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BT - 2021 14th International Conference on Developments in eSystems Engineering, DeSE 2021

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 14th International Conference on Developments in eSystems Engineering, DeSE 2021

Y2 - 7 December 2021 through 10 December 2021

ER -

Jarndal A, Husain S, Diab MS, Shikhli A. Machine Learning Based Prediction Models for the Percentage Deaths Due to COVID-19. In 2021 14th International Conference on Developments in eSystems Engineering, DeSE 2021. Institute of Electrical and Electronics Engineers Inc. 2021. p. 418-423. (Proceedings - International Conference on Developments in eSystems Engineering, DeSE). doi: 10.1109/DESE54285.2021.9719584

Machine Learning Based Prediction Models for the Percentage Deaths Due to COVID-19

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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