A methodology for the automated creation of fuzzy expert systems for ischaemic and arrhythmic beat classification based on a set of rules obtained by a decision tree英文资料.pdf

ARTMED-935; No of Pages 14 Artificial Intelligence in Medicine (2007) xxx, xxx—xxx /journals/aiim A methodology for the automated creation of fuzzy expert systems for ischaemic and arrhythmic beat classification based on a set of rules obtained by a decision tree Themis P. Exarchos a,b, Markos G. Tsipouras a, Costas P. Exarchos a, Costas Papaloukas a,c, Dimitrios I. Fotiadis a,d,e,*, Lampros K. Michalis e,f a Unit of Medical Technology and Intelligent Information Systems, Department of Computer Science, University of Ioannina, GR 45110 Ioannina, Greece b Department of Medical Physics, Medical School, University of Ioannina, GR 45110 Ioannina, Greece c Department of Biological Applications and Technology, University of Ioannina, GR 45110 Ioannina, Greece d Biomedical Research Institute-FORTH, GR 45110 Ioannina, Greece e Michaelideion Cardiology Centre, GR 45110 Ioannina, Greece f Department of Cardiology, Medical School, University of Ioannina, GR 45110 Ioannina, Greece Received 6 October 2006; received in revised form 19 February 2007; accepted 5 April 2007 KEYWORDS Summary Fuzzy expert system; Data mining; Objective: In the current work we propose a methodology for the automated creation Optimization; of fuzzy expert systems, applied in ischaemic and arrhythmic beat classification. Ischaemia; Methods: The proposed methodology automatically creates a fuzzy expert system Arrhythmia from an initial training dataset. The approach consists of three stages: (a) extraction of a crisp set of rules from a decision tree induced from the training dataset, (b) transformation of the crisp set of rules into a fuzzy model and (c) optimization of the