Development of a Fuzzy Logic-based Model for Monitoring Cardiovascular Risk

dc.contributor.authoridowu, PETER ADEBAYO
dc.contributor.authorbalogun, JEREMIAH ADEMOLA
dc.contributor.authorogunlade, oluwadare
dc.date.accessioned2023-05-13T17:50:50Z
dc.date.available2023-05-13T17:50:50Z
dc.date.issued2015-10
dc.descriptionvol:2015 issue no:10(4):38-55 doi:10.4018/IJHISI.2015100103 p.54en_US
dc.description.abstractCardiovascular diseases (CVD) are top killers with heart failure as one of the most leading cause of death in both developed and developing countries. In Nigeria, the inability to consistently monitor the vital signs of patients has led to the hospitalization and untimely death of many as a result of heart failure. Fuzzy logic models have found relevance in healthcare services due to their ability to measure vagueness associated with uncertainty management in intelligent systems. This study aims to develop a fuzzy logic model for monitoring heart failure risk using risk indicators assessed from patients. Following interview with expert cardiologists, the different stages of heart failure was identified alongside their respective indicators. Triangular membership functions were used to fuzzify the input and output variables while the fuzzy inference engine was developed using rules elicited from cardiologists. The model was simulated using the MATLABĀ® Fuzzy Logic Toolbox.en_US
dc.identifier.urihttps://ir.oauife.edu.ng/123456789/5506
dc.language.isoen_USen_US
dc.subjectfuzzy logicen_US
dc.subjectcardiovascular diseaseen_US
dc.subjectmonitoring systemen_US
dc.subjectheart failureen_US
dc.subjectrisk modellingen_US
dc.titleDevelopment of a Fuzzy Logic-based Model for Monitoring Cardiovascular Risken_US
dc.typeJournalen_US
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