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Fuzzy Logic Inference System for Managing Intensive Care Unit Resources Based on Knowledge Graph

Ahmad F Subahi*, Areej Athama

Department of Computer Science, University College of Al Jamoum, Umm Al-Qura University, Makkah, 21421, Saudi Arabia

* Corresponding Author: Ahmad F Subahi. Email: email

(This article belongs to the Special Issue: Smart Solutions to Develop New Technologies for Healthcare)

Computers, Materials & Continua 2023, 77(3), 3801-3816. https://doi.org/10.32604/cmc.2023.034522

Abstract

With the rapid growth in the availability of digital health-related data, there is a great demand for the utilization of intelligent information systems within the healthcare sector. These systems can manage and manipulate this massive amount of health-related data and encourage different decision-making tasks. They can also provide various sustainable health services such as medical error reduction, diagnosis acceleration, and clinical services quality improvement. The intensive care unit (ICU) is one of the most important hospital units. However, there are limited rooms and resources in most hospitals. During times of seasonal diseases and pandemics, ICUs face high admission demand. In line with this increasing number of admissions, determining health risk levels has become an essential and imperative task. It creates a heightened demand for the implementation of an expert decision support system, enabling doctors to accurately and swiftly determine the risk level of patients. Therefore, this study proposes a fuzzy logic inference system built on domain-specific knowledge graphs, as a proof-of-concept, for tackling this healthcare-related issue. The system employs a combination of two sets of fuzzy input parameters to classify health risk levels of new admissions to hospitals. The proposed system implemented utilizes MATLAB Fuzzy Logic Toolbox via several experiments showing the validity of the proposed system.

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APA Style
Subahi, A.F., Athama, A. (2023). Fuzzy logic inference system for managing intensive care unit resources based on knowledge graph. Computers, Materials & Continua, 77(3), 3801-3816. https://doi.org/10.32604/cmc.2023.034522
Vancouver Style
Subahi AF, Athama A. Fuzzy logic inference system for managing intensive care unit resources based on knowledge graph. Comput Mater Contin. 2023;77(3):3801-3816 https://doi.org/10.32604/cmc.2023.034522
IEEE Style
A.F. Subahi and A. Athama, "Fuzzy Logic Inference System for Managing Intensive Care Unit Resources Based on Knowledge Graph," Comput. Mater. Contin., vol. 77, no. 3, pp. 3801-3816. 2023. https://doi.org/10.32604/cmc.2023.034522



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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