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Optimizing ICU Resource Allocation During the COVID-19 Crisis: An AI-Driven Approach
Research Article | Published: 02 June 2025
Biomedical Informatics and Smart Healthcare Volume 1, Issue 1, 2025: 9-17
Volume 1, Issue 1, Biomedical Informatics and Smart Healthcare
Volume 1, Issue 1, 2025
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Biomedical Informatics and Smart Healthcare, Volume 1, Issue 1, 2025: 9-17

Open Access | Research Article | 02 June 2025
Optimizing ICU Resource Allocation During the COVID-19 Crisis: An AI-Driven Approach
by
Salma Sabrou Salma Sabrou 1
Azidine Guezzaz Azidine Guezzaz 1 *
Vinayakumar Ravi Vinayakumar Ravi 2
Said Benkirane Said Benkirane 1
Mourade Azrour Mourade Azrour 3
1 LaRTiD Laboratory, Higher School of Technology, Cadi Ayyad University, Marrakesh 40000, Morocco
2 Center for Artificial Intelligence, Prince Mohammad Bin Fahd University, Al Khobar 31952, Saudi Arabia
3 Faculty of Sciences and Technics, Moulay Ismail University, Meknes BP 298, Morocco
* Corresponding Author: Azidine Guezzaz, [email protected]
DOI: 10.62762/BISH.2025.457428
Received: 02 April 2025, Accepted: 10 May 2025, Published: 02 June 2025  
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Abstract
The COVID-19 pandemic exerted immense pressure on healthcare systems globally, including in Morocco, where the demand for intensive care unit (ICU) beds frequently surpassed available capacity—at times doubling it. This crisis underscored the critical need for accurate prediction of ICU length of stay (LOS) to optimize resource allocation, enhance patient care, and reduce healthcare costs. This study aims to leverage artificial intelligence (AI) to predict and optimize ICU resource allocation during the COVID-19 crisis, ensuring efficient patient triage and resource management. By integrating Random Forest (RF) and Deep Neural Networks (DNN), the research demonstrates improved accuracy in predicting patient LOS, thereby facilitating better resource management and patient care optimization. Furthermore, the study emphasizes the necessity for AI models to be interpretable and user-friendly to ensure successful adoption by healthcare professionals.
Graphical Abstract
Optimizing ICU Resource Allocation During the COVID-19 Crisis: An AI-Driven Approach
Keywords
machine learning
deep learning
ICU
patient care
prediction
decision making
Data Availability Statement
Data will be made available on request.
Funding
This work was supported without any funding.
Conflicts of Interest
The authors declare no conflicts of interest.
Ethical Approval and Consent to Participate
Not applicable.
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Cite This Article
APA Style
Sabrou, S., Guezzaz, A., Ravi, V., Benkirane, S., & Azrour, M. (2025). Optimizing ICU Resource Allocation During the COVID-19 Crisis: An AI-Driven Approach. Biomedical Informatics and Smart Healthcare, 1(1), 9–17. https://doi.org/10.62762/BISH.2025.457428
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CC BY Copyright © 2025 by the Author(s). Published by Institute of Emerging and Computer Engineers. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.
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