Applying Rough Set Theory to Multi Stage Medical Diagnosing

Article type: Research Article

Authors: Wakulicz-Deja, Alicja | Peszek, Piotr

Affiliations: Institute of Computer Science, University of Silesia, Bedzińska 39, 41-200 Sosnowiec, Poland

Abstract: The work contains an example of application of Rough Set Theory to decision making – diagnosing Mitochondrial Encephalomyopathies (MEM) for children. The resulting decision support system maximally limits the indications for invasive diagnostic methods (puncture, muscle and/or nerve specimens). Moreover, it shortens the time necessary for making diagnosis. The system has been developed on the basis of data obtained from the II Clinic Department of Pediatrics of the Silesian Academy of Medicine (further referred to as the Clinic of Pediatrics).

Keywords: machine learning, mitochondrial encephalomyopathies, rough sets

Journal: Fundamenta Informaticae, vol. 54, no. 4, pp. 387-408, 2003