Decision Support Systems for Cardiovascular Diseases Based on Data Mining and Fuzzy Modelling

Decision Support Systems for Cardiovascular Diseases Based on Data Mining and Fuzzy Modelling

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 and Biomedical Research Institute, Greece), Aris Bechlioulis (University of Ioannina, Greece and Michaelideion Cardiology Center, Greece) and Katerina K. Naka (University of Ioannina, Greece and Michaelideion Cardiology Center, Greece)
Copyright: © 2008 |Pages: 9
DOI: 10.4018/978-1-59904-889-5.ch051
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Abstract

This article addresses the decision support regarding cardiovascular diseases, using computer-based methods, focusing on the coronary artery disease (CAD) diagnosis and on the prediction of clinical restenosis in patients undergoing angioplasty. Methods reported in the literature are reviewed with respect to (i) the medical information that are employing in order to reach the diagnosis and (ii) the data analysis techniques used for the creation of the CDSSs. In what concerns medical information, easily and noninvasively-obtained data present several advantages compared to other types of data, while data analysis techniques that are characterized by transparency regarding their decisions are more suitable for medical decision making. A recently developed approach that complies with the above requirements is presented. The approach is based on data mining and fuzzy modelling. Using this approach, one CDSS has been developed for each of the two cardiovascular problems mentioned above. These CDSSs are extensively evaluated and comments about the discovered knowledge are provided by medical experts. The later is of great importance in designing and evaluating CDSSs, since it allows them to be integrated into real clinical environments.

Key Terms in this Chapter

Data Mining: The process of extracting previously unknown and potentially useful knowledge, hidden in large volumes of data.

Artificial Neural Network: An interconnected group of artificial neurons that uses a mathematical or computational model for information processing based on a connectionist approach to computation.

Coronary Artery Disease: The narrowing of the coronary arteries, sufficiently to prevent adequate blood supply to the heart muscle. It is usually caused by atherosclerosis and may progress to the damage of heart muscle.

Inference Engine: The part of a decision support system that performs the reasoning function.

Fuzzy Logic: A way of reasoning that can cope with uncertain or partial information.

Clinical Restenosis: Death presumably from cardiac causes, myocardial infarction not attributable to another coronary artery than the target vessel, and target vessel revascularization either by repeat PTCA or CABG.

Clinical Decision Support Systems (CDSS): Computer based methods that aim to assist clinicians in decision making. The core of CDSSs is an inference engine that can generate case specific advice based on medical data.

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