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DOI Prefix: 10.47001/IRJIET

Review Paper on Machine Learning-Based Forecasting of COVID-19 Cases and Hospitalization

Er. Akashdeep Singh RanaPh.D Scholar, Department of Computer Science Engineering & Technology, Sant Baba Bhag Singh University, Jalandhar, Punjab, IndiaDr. Jagdeep KaurProfessor, Department of Computer Science Engineering & Technology, Sant Baba Bhag Singh University, Jalandhar, Punjab, India

Vol 8 No 11 (2024): Volume 8, Issue 11, November 2024 | Pages: 309-312

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 06-01-2025

doi Logo doi.org/10.47001/IRJIET/2024.811040

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Abstract

The COVID-19 pandemic has prompted a global health crisis, overwhelming healthcare systems and demanding innovative approaches to manage resources effectively. Machine learning (ML) has emerged as a critical tool for forecasting the trajectory of COVID-19 cases and hospitalizations, offering data-driven insights for timely decision-making. This review presents an overview of the most recent studies on ML-based forecasting models for predicting COVID-19 cases and hospitalizations. We explore various techniques, including regression models, time series analysis, and deep learning approaches, as well as their strengths, challenges, and potential for future advancements. This review also highlights the importance of accurate predictions for managing healthcare infrastructure and planning responses to the pandemic.

Keywords

Machine Learning, Covid-19, Hospitalization, COVID-19 Cases, ML-based forecasting


Citation of this Article

Er. Akashdeep Singh Rana, & Dr. Jagdeep Kaur. (2024). Review Paper on Machine Learning-Based Forecasting of COVID-19 Cases and Hospitalization. International Research Journal of Innovations in Engineering and Technology - IRJIET, 8(11), 309-312. Article DOI: https://doi.org/10.47001/IRJIET/2024.811040

Licence Copyright (c) 2026 International Research Journal of Innovations in Engineering and Technology creative common licence This work is licensed under Creative common Attribution Non Commercial 4.0 Internation Licence
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