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DOI: 10.14569/IJACSA.2023.0140493
PDF

Discovering COVID-19 Death Patterns from Deceased Patients: A Case Study in Saudi Arabia

Author 1: Abdulrahman Alomary
Author 2: Tarik Alafif
Author 3: Abdulmohsen Almalawi
Author 4: Anas Hadi
Author 5: Faris Alkhilaiwi
Author 6: Yasser Alatawi

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 14 Issue 4, 2023.

  • Abstract and Keywords
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Abstract: COVID-19 is a serious infection that cause severe injuries and deaths worldwide. The COVID-19 virus can infect people of all ages, especially the elderly. Furthermore, elderly who have co-morbid conditions (e.g., chronic conditions) are at an increased risk of death. At the present time, no approach exists that can facilitate the characterization of patterns of COVID-19 death. In this study, an approach to identify patterns of COVID- 19 death efficiently and systematically is applied by adapting the Apriori algorithm. Validation and evaluation of the proposed approach are based on a robust and reliable dataset collected from Health Affairs in the Makkah region of Saudi Arabia. The study results show that there are strong associations between hypertension, diabetes, cardiovascular disease, and kidney disease and death among COVID-19 deceased patients.

Keywords: COVID-19; association rules; Apriori algorithm; patterns; death; chronic diseases

Abdulrahman Alomary, Tarik Alafif, Abdulmohsen Almalawi, Anas Hadi, Faris Alkhilaiwi and Yasser Alatawi, “Discovering COVID-19 Death Patterns from Deceased Patients: A Case Study in Saudi Arabia” International Journal of Advanced Computer Science and Applications(IJACSA), 14(4), 2023. http://dx.doi.org/10.14569/IJACSA.2023.0140493

@article{Alomary2023,
title = {Discovering COVID-19 Death Patterns from Deceased Patients: A Case Study in Saudi Arabia},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.0140493},
url = {http://dx.doi.org/10.14569/IJACSA.2023.0140493},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {4},
author = {Abdulrahman Alomary and Tarik Alafif and Abdulmohsen Almalawi and Anas Hadi and Faris Alkhilaiwi and Yasser Alatawi}
}



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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