Fuzzy Logic Inference System for Managing Intensive Care Unit Resources Based on Knowledge Graph
作者机构：Department of Computer ScienceUniversity College of Al JamoumUmm Al-Qura UniversityMakkah21421Saudi Arabia
出 版 物：《Computers, Materials & Continua》 (计算机、材料和连续体（英文）)
年 卷 期：2023年第77卷第12期
页 面：3801-3816页
核心收录：
学科分类：081203[工学-计算机应用技术] 08[工学] 0835[工学-软件工程] 0812[工学-计算机科学与技术（可授工学、理学学位）]
基 金：funded by the Deanship of Scientific Research at Umm Al-Qura University Makkah Kingdom of Saudi Arabia.Under Grant Code:22UQU4281755DSR05
主 题：Fuzzy logic role-based expert system decision-support system knowledge graph Internet of Things ICU resource management Neo4J graph database
摘 要：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 *** systems can manage and manipulate this massive amount of health-related data and encourage different decision-making *** can also provide various sustainable health services such as medical error reduction,diagnosis acceleration,and clinical services quality *** intensive care unit(ICU)is one of the most important hospital ***,there are limited rooms and resources in most *** times of seasonal diseases and pandemics,ICUs face high admission *** line with this increasing number of admissions,determining health risk levels has become an essential and imperative *** creates a heightened demand for the implementation of an expert decision support system,enabling doctors to accurately and swiftly determine the risk level of ***,this study proposes a fuzzy logic inference system built on domain-specific knowledge graphs,as a proof-of-concept,for tackling this healthcare-related *** system employs a combination of two sets of fuzzy input parameters to classify health risk levels of new admissions to *** proposed system implemented utilizes MATLAB Fuzzy Logic Toolbox via several experiments showing the validity of the proposed system.
维普期刊数据库