Affiliations: K.Marcinkowski University of Medical Sciences in
Poznań, 3 Szwajcarska Str., 61-285 Poznań, Poland | Institute of Computing Science, Poznań University of
Technology, 3A Piotrowo Str., 60-965 Poznań, Poland | Trauma and Orthopaedic Department, MSW Hospital, 34
Dojazd Str., 60-631 Poznań, Poland
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.
