Analysis of a Dobutamine Stress Echocardiography Dataset Using Rough Sets

Authors:
Kenneth R. Revett
Affiliations:
University of Westminster, Harrow School of Computer Science, London,HA1 3TP, England
Venue:
RSEISP '07 Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms
Year:
2007

Citing 2
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Diagnostic Feature Analysis of a Dobutamine Stress Echocardiography Dataset Using Rough Sets

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International Journal of Healthcare Information Systems and Informatics

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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.