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dc.contributor.authorMaftouni, Maede-
dc.contributor.authorZarandi, Mohammad Hossein Fazel-
dc.contributor.authorTürkşen, İsmail Burhan-
dc.contributor.authorRoshani, Faezeh-
dc.identifier.citationAnnual Meeting of the North-American-Fuzzy-Information-Processing-Society (NAFIPS) -- AUG 17-19, 2015 -- Digipen, WAen_US
dc.description.abstractAnkylosing spondylitis (AS) is a chronic inflammatory disease. The pathogenesis of AS is poorly understood. However its association with human leukycyte antigen (HLA)-B27 is known. AS causes significant pain, disability, and social burden around the world [1]. Early diagnosis and treatment of AS are necessary in order to prevent or reduce all types of costs associated with loss of function. If the diagnosis is missed, however, the quality of patient's life will degrade. Besides, as a positive family history of AS is a strong risk factor for the disease, this negligence will put other family member's in jeopardy. Nowadays, Expert systems play a big role in diagnosis of patients with different diseases. The application of expert system to diagnose diseases started in the 70s with the development of Mycin. Expert systems in medical diagnosis can help in storing more knowledge than before and make it accessible in absence of a specialist and increase distribution of expertise. Our goal in this paper is to design a type-2 fuzzy rule-based expert system for AS diagnosis where the rules are evidence-based. The basic aim of evidence-based practice is to establish a narrow set of criteria for diagnosis based on research studies. System has mainly two parts. Firstly, the suspicion of disease is assessed for the persons identity according to odds ratio studies and patient's family history. Then the modified New York criteria (1984) for exploring sign and symptoms and the HLA-B27 examination result are considered. The system benefits from fuzzy reasoning and can manage the uncertain inputs through fuzzifying them and making use of type-2 fuzzy rules. Moreover, the system is connected to a spreadsheet for storing the patient's input data and system's final diagnosis. This system can be used by a non-rheumatologist in the diagnosis of AS or by a rheumatologist as an assistant.en_US
dc.description.sponsorshipIEEE Advancing Tech Humanity, N Amer Fuzzy Informat Proc Socen_US
dc.relation.ispartof2015 Annual Meeting of The North American Fuzzy Information Processing Society Digipen Nafips 2015en_US
dc.subjecttype-2 fuzzy rule-baseden_US
dc.subjectexpert systemen_US
dc.subjectevidence-based practiceen_US
dc.subjectmedical diagnosisen_US
dc.subjectAnkylosing spondylitisen_US
dc.titleType-2 Fuzzy Rule-based Expert System for Ankylosing spondylitis Diagnosisen_US
dc.typeConference Objecten_US
dc.departmentFaculties, Faculty of Engineering, Department of Industrial Engineeringen_US
dc.departmentFakülteler, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümütr_TR
dc.institutionauthorTürkşen, İsmail Burhan-
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.relation.conferenceAnnual Meeting of the North-American-Fuzzy-Information-Processing-Society (NAFIPS)en_US
item.fulltextNo Fulltext-
item.openairetypeConference Object-
Appears in Collections:Endüstri Mühendisliği Bölümü / Department of Industrial Engineering
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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