title: Development and evaluation of fuzzy criteria for the diagnosis of rheumatoid arthritis.
abstract: In 1987, the American Rheumatism Association issued a set of criteria for the classification of rheumatoid arthritis (RA) to provide a uniform definition of RA patients. Fuzzy set theory and fuzzy logic were used to transform this set of criteria into a diagnostic tool that offers diagnoses at different levels of confidence: a definite level, which was consistent with the original criteria definition, as well as several possible and superdefinite levels. Two fuzzy models and a reference model which provided results at a definite level only were applied to 292 clinical cases from a hospital for rheumatic diseases. At the definite level, all models yielded a sensitivity rate of 72.6% and a specificity rate of 87.0%. Sensitivity and specificity rates at the possible levels ranged from 73.3% to 85.6% and from 83.6% to 87.0%. At the superdefinite levels, sensitivity rates ranged from 39.0% to 63.7% and specificity rates from 90.4% to 95.2%. Fuzzy techniques were helpful to add flexibility to preexisting diagnostic criteria in order to obtain diagnoses at the desired level of confidence.
authors.affiliation: Department of Medical Computer Sciences, University of Vienna, Austria.
authors.forename: H
authors.initials: H
authors.lastname: Leitich
authors.forename: K P
authors.initials: KP
authors.lastname: Adlassnig
authors.forename: G
authors.initials: G
authors.lastname: Kolarz
mesh_terms: D001172:Arthritis, Rheumatoid / Q000145:classification / Q000175:diagnosis*; D003936:Diagnosis, Computer-Assisted; D005103:Expert Systems; D017143:Fuzzy Logic; D006801:Humans; D008962:Models, Theoretical; D015203:Reproducibility of Results; D012985:Software Design