Abstract
Stress echocardiography is an important functional diagnosis and prognostic tool that is now routinely applied to evaluate the risk of cardiovascular artery disease (CAD). A complete dataset containing data on 558 subjects undergoing a prospective longitudinal study is employed to investigate what attributes correlate with the final outcome. The dataset was examined using rough sets, which resulted in a series of decision rules that predict which attributes influence the outcomes measured clinically and recorded in the dataset. The results indicate that the ECG attribute was very informative. In addition, prehistory information has a significant impact on the classification accuracy.
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Revett, K.R. (2007). Analysis of a Dobutamine Stress Echocardiography Dataset Using Rough Sets. In: Kryszkiewicz, M., Peters, J.F., Rybinski, H., Skowron, A. (eds) Rough Sets and Intelligent Systems Paradigms. RSEISP 2007. Lecture Notes in Computer Science(), vol 4585. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73451-2_79
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DOI: https://doi.org/10.1007/978-3-540-73451-2_79
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73450-5
Online ISBN: 978-3-540-73451-2
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