Predict Covid-19 Pandemic Phases using Several Machine Learning Algorithms
COVID-19, despite the worldwide reduced mortality and severity, is still a menace all over the world. This paper also provides the outline of a classification of pandemic stages and describes the methods for using machine learning to evaluate present-day pandemic intensity. Some aspects that have been targeted are economic and educational status and health, both physical and mental, concerning different aspects of life in Malaysia. The chosen algorithms for our analysis include SVM, PA, KNN, AdaBoost, DT, ETs, RF, GB, HGB, and MLP, with the MLP showing the best results. This strategy may be applied to the following pandemics where possible to make comparisons and to make conclusions and come up with more concrete models to be applied to any other communicable diseases.
Authors
- Ahmed Awad (ORCID: https://orcid.org/0009-0005-3470-7404)
- Yasir Hussein Shakir (ORCID: https://orcid.org/0009-0006-1188-8326)
- Eshaq Aziz Awadh AL Mandhari (ORCID: https://orcid.org/0009-0003-7283-0281)
- Issa Nasser Salim Al-ghatrifi
Institutions
- Asia Pacific University of Technology & Innovation (MY)
- University of Nizwa (OM)
- Al-Zahra College for Women (OM)
Publication Details
- Journal
- East Journal of Computer Science
- Published
- 2025-05-27
- DOI
- https://doi.org/10.63496/ejcs.vol1.iss3.96
- Primary Topic
- COVID-19 diagnosis using AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00