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Decision Support Systems for Cardiovascular Diseases Based on Data Mining and Fuzzy Modelling
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Author(s): Markos G. Tsipouras (University of Ioannina, Greece), Themis P. Exarchos (University of Ioannina, Greece), Dimitrios I. Fotiadis (University of Ioannina, Greece, Michaelideion Cardiology Center, Greece, & Biomedical Research Institute, Greece)and Aris Bechlioulis (University of Ioannina, Greece)
Copyright: 2010
Pages: 11
Source title:
Strategic Information Systems: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): M. Gordon Hunter (University of Lethbridge, Canada)
DOI: 10.4018/978-1-60566-677-8.ch097
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Abstract
The widespread availability of new computational methods and tools for data analysis and predictive modelling requires medical informatics researchers and practitioners to systematically select the most appropriate strategy to cope with clinical prediction problems. In particular, data mining techniques offer methodological and technical solutions to deal with the analysis of medical data and construction of decision support systems. Furthermore, fuzzy modelling deals with the ambiguity inherent in all medical problems. These methods can be used to design and develop clinical decision support systems (CDSSs), which, after evaluated from the experts, can be integrated into clinical environments.
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