Application of rule induction and rough sets to verification of magnetic resonance diagnosis

Authors:
Krzysztof Słowiński;Jerzy Stefanowski;Dariusz Siwiński
Affiliations:
Head of Division of Trauma, Burns and Plastic Surgery, 2nd Department of Surgery, Division of Trauma, K.Marcinkowski University of Medical Sciences in Poznań, 3 Szwajcarska Str., 61-285 Pozna ...;Institute of Computing Science, Poznan University of Technology, 3A Piotrowo Str., 60-965 Poznan, Poland;Trauma and Orthopaedic Department, MSW Hospital, 34 Dojazd Str., 60-631 Poznan, Poland
Venue:
Fundamenta Informaticae
Year:
2002

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Abstract

We discuss a process of analysing medical diagnostic data by means of the combined rule induction and rough set approach. The first step of this analysis includes the use of various techniques for discretization of numerical attributes. Rough sets theory is applied to determine attribute importance for the patients' classification. The novel contribution concerns considering two different algorithms inducing either minimum or satisfactory set of decision rules. Verification of classification abilities of these rule sets is extended by an examination of sensitivity and specificity measures. Moreover, a comparative study of these composed approaches against other learning systems is discussed. The approach is illustrated on a medical problem concerning anterior cruciate ligament (ACL) rupture in a knee. The patients are described by attributes coming from anamnesis, MR examinations and verified by arthroscopy. The clinical impact of our research is indicating two attributes (PCL index, age) and their specific values that could support a physician in resigning from performing arthroscopy for some patients.