A Linguistic Fuzzy Expert System for Contagious Diseases Detection and Isolation

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dc.contributor.authorOsigbemeh, M.S
dc.contributor.authorOgunwolu, F.O
dc.contributor.authorOmoare, A.A
dc.contributor.authorInyiama, H.C
dc.date.accessioned2019-03-04T13:47:54Z
dc.date.available2019-03-04T13:47:54Z
dc.date.issued2014
dc.descriptionJournal Articlesen_US
dc.description.abstractThis paper presents an electronic Expert system platform to detect and diagnose existing and new cases of contagious diseases as they occur with minimal contact with the index patient(s) and healthcare personnel with a confidence level that can be used to initiate or suggest appropriate follow-up action(s). The aim is to use ICT tools for patient-diagnosis, raise a red flag in real-time and thus contain contagious cases which may degenerate into an epidemic by providing a way to analyze vague and ambiguous input data from visible and reported symptoms in patients. A re-useable Expert system which makes use of fuzzy reasoning techniques and design methodology was used in this work. The Expert system is premised on rule-based fuzzy logic which captures the ambiguity, imprecision and nuances involved in disease reporting and detection using the Mamdani model. The software developed for the Fuzzy Expert system, called SOSIC, presents its diagnosis with fuzzy values between 0 to 1 corresponding to its level of confidence for the fuzzy inputs. The current approach to e-diagnosis and detection of contagious diseases using the SOSIC software is not completely contactless, thus ongoing investigations are geared towards improving SOSIC to be contactless. The developed system which runs on a computer system provides a safe procedure with minimum contact between patients and healthcare personnel to address early detection and diagnosis issues that may help forestall chain-infection and epidemics. The fuzzy based Expert system can be further extended to accommodate the detection of a wider array of symptoms as new cases arise; thus this paper fulfils an identified need in safe healthcare practice.en_US
dc.description.sponsorshipTertiary Education Trust Funden_US
dc.identifier.citationOsigbemeh, M.S, Ogunwolu, F.O, Omoare, A.A and Inyiama, H.C (2014). A Linguistic Fuzzy Expert System for Contagious Diseases Detection and Isolation. Unilag Journal of Medicine, Science and Technology, Vol.2 (1&2), 1-10p.en_US
dc.identifier.issn2408-5049
dc.identifier.urihttps://ir.unilag.edu.ng/handle/123456789/3884
dc.language.isoenen_US
dc.publisherUniversity of Lagos Press, Akokaen_US
dc.relation.ispartofseriesUniversity of lagos Journal;Vol.2 (1&2)
dc.subjectQuarantiningen_US
dc.subjectPreventing Diseasesen_US
dc.subjectSOSIC Diagnosisen_US
dc.subjectContagious Diseases Controlen_US
dc.subjectFuzzy Expert Systemsen_US
dc.titleA Linguistic Fuzzy Expert System for Contagious Diseases Detection and Isolationen_US
dc.typeArticleen_US
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Volume 2, Issue 1 & 2, 2014