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Rule based fuzzy logic approach for classification of fibromyalgia syndrome

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dc.contributor.authors Arslan, E; Yildiz, S; Albayrak, Y; Koklukaya, E;
dc.date.accessioned 2020-02-27T07:00:39Z
dc.date.available 2020-02-27T07:00:39Z
dc.date.issued 2016
dc.identifier.citation Arslan, E; Yildiz, S; Albayrak, Y; Koklukaya, E; (2016). Rule based fuzzy logic approach for classification of fibromyalgia syndrome. AUSTRALASIAN PHYSICAL & ENGINEERING SCIENCES IN MEDICINE, 39, 515-501
dc.identifier.issn 0158-9938
dc.identifier.uri https://doi.org/10.1007/s13246-016-0452-z
dc.identifier.uri https://hdl.handle.net/20.500.12619/64810
dc.description.abstract Fibromyalgia syndrome (FMS) is a chronic muscle and skeletal system disease observed generally in women, manifesting itself with a widespread pain and impairing the individual's quality of life. FMS diagnosis is made based on the American College of Rheumatology (ACR) criteria. However, recently the employability and sufficiency of ACR criteria are under debate. In this context, several evaluation methods, including clinical evaluation methods were proposed by researchers. Accordingly, ACR had to update their criteria announced back in 1990, 2010 and 2011. Proposed rule based fuzzy logic method aims to evaluate FMS at a different angle as well. This method contains a rule base derived from the 1990 ACR criteria and the individual experiences of specialists. The study was conducted using the data collected from 60 inpatient and 30 healthy volunteers. Several tests and physical examination were administered to the participants. The fuzzy logic rule base was structured using the parameters of tender point count, chronic widespread pain period, pain severity, fatigue severity and sleep disturbance level, which were deemed important in FMS diagnosis. It has been observed that generally fuzzy predictor was 95.56 % consistent with at least of the specialists, who are not a creator of the fuzzy rule base. Thus, in diagnosis classification where the severity of FMS was classified as well, consistent findings were obtained from the comparison of interpretations and experiences of specialists and the fuzzy logic approach. The study proposes a rule base, which could eliminate the shortcomings of 1990 ACR criteria during the FMS evaluation process. Furthermore, the proposed method presents a classification on the severity of the disease, which was not available with the ACR criteria. The study was not limited to only disease classification but at the same time the probability of occurrence and severity was classified. In addition, those who were not suffering from FMS were evaluated for their conditions in other patient groups.
dc.language English
dc.publisher SPRINGER
dc.subject Engineering
dc.title Rule based fuzzy logic approach for classification of fibromyalgia syndrome
dc.type Article
dc.identifier.volume 39
dc.identifier.startpage 501
dc.identifier.endpage 515
dc.contributor.department Sakarya Üniversitesi/Mühendislik Fakültesi/Elektrik-Elektronik Mühendisliği Bölümü
dc.contributor.saüauthor Arslan, Evren
dc.contributor.saüauthor Köklükaya, Etem
dc.relation.journal AUSTRALASIAN PHYSICAL & ENGINEERING SCIENCES IN MEDICINE
dc.identifier.wos WOS:000379039800016
dc.identifier.doi 10.1007/s13246-016-0452-z
dc.identifier.eissn 1879-5447
dc.contributor.author Arslan, Evren
dc.contributor.author Sedat Yildiz
dc.contributor.author Yalcin Albayrak
dc.contributor.author Köklükaya, Etem


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