Design of a fuzzy expert system for diagnosis of rheumatoid arthritis

Özet

The disease of Rheumatoid Arthritis (RA) is a systemic, chronic, and autoimmune inflammatory rheumatic disease which is seen in multiple joints at the same time and has an unknown aetiology, and of which clinical course varies from patient to patient. The early recognition and the knowledge of severity of the RA disease is very important for treatment to be conducted. The physical examination of the patient, laboratory tests, and medical story are needed to diagnose the condition of Rheumatoid Arthritis. The laboratory findings to be used in the diagnosis of the disease are not specific to Rheumatoid Arthritis, and these findings are used to support the diagnosis made according to the clinical indications and in evaluating the course of the disease. In this thesis, a Fuzzy Expert System (FES) is designed to assist doctors in diagnosing the disease and to help doctors make decisions by getting help from a specialist in his field of study. For this FES, it has been used the laboratory tests of CRP (C-Reactive Protein), Sedim, RF (Rheumatoid Factor), and ANA (Anti-Nuclear Antibody) that were determined the specialist. The system has been designed by the results of these tests, the medical stories of the patients, and the specialist doctor’s views using the MATLAB program, and its accuracy has been checked. Uniting the FES result with the patient’s story and the values of Anti-CCP (Anti Cyclic Citrullinated Peptide Antibody), it has been concluded in the diagnosis of RA disease. A website has been published for the use of doctors and patients by the designed FES was coded in a web-based PHP programming language. It has been found that the diagnosis made on the basis of the FES via the website, the diagnosis by the specialist doctors, and the diagnosis made according to 2010 ACR / EULAR Rheumatoid Arthritis Classification Criteria are compatible with each other, and the system has been approved by the specialist doctor. Keywords: Disease Diagnosis, Expert System, Fuzzy Expert System, Rheumatoid Arthritis