title: Knowledge discovery with classification rules in a cardiovascular dataset.
abstract: In this paper we study an evolutionary machine learning approach to data mining and knowledge discovery based on the induction of classification rules. A method for automatic rules induction called AREX using evolutionary induction of decision trees and automatic programming is introduced. The proposed algorithm is applied to a cardiovascular dataset consisting of different groups of attributes which should possibly reveal the presence of some specific cardiovascular problems in young patients. A case study is presented that shows the use of AREX for the classification of patients and for discovering possible new medical knowledge from the dataset. The defined knowledge discovery loop comprises a medical expert's assessment of induced rules to drive the evolution of rule sets towards more appropriate solutions. The final result is the discovery of a possible new medical knowledge in the field of pediatric cardiology.
authors.affiliation: University of Maribor - FERI, Smetanova 17, SI-2000 Maribor, Slovenia. vili.podgorelec@uni-mb.si
authors.forename: Vili
authors.initials: V
authors.lastname: Podgorelec
authors.forename: Peter
authors.initials: P
authors.lastname: Kokol
authors.forename: Milojka Molan
authors.initials: MM
authors.lastname: Stiglic
authors.forename: Marjan
authors.initials: M
authors.lastname: Hericko
authors.forename: Ivan
authors.initials: I
authors.lastname: Rozman
mesh_terms: D000465:Algorithms; D002319:Cardiovascular System; D002648:Child; D006801:Humans; D016247:Information Storage and Retrieval; D051188:Knowledge Bases