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Methods Inf Med 1996; 35(04/05): 334-342
DOI: 10.1055/s-0038-1634678
Original Article
Schattauer GmbH

Development and Evaluation of Fuzzy Criteria for the Diagnosis of Rheumatoid Arthritis

H. Leitich
1   Department of Medical Computer Sciences, University of Vienna, Baden, Austria
,
K.-P. Adlassnig
1   Department of Medical Computer Sciences, University of Vienna, Baden, Austria
,
G. Kolarz
2   Clinic for Rheumatic Diseases of the Social Insurance Company for Trade and Industry, Baden, Austria
3   Institute for Rheumatology in Baden, Austria
› Author Affiliations
Further Information

Publication History

Publication Date:
20 February 2018 (online)

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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.

Keywords:

Fuzzy Set Theory - Expert Systems - Diagnosis - Rheumatoid Arthritis - CADIAG-2
 

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