Multi-parametric Diagnosis Indexes and Emerging Pattern based Classification Technique for Diagnosing Cardiovascular Disease


The KIPS Transactions:PartD, Vol. 16, No. 1, pp. 11-26, Feb. 2009
10.3745/KIPSTD.2009.16.1.11,   PDF Download:

Abstract

In order to diagnose cardiovascular disease, we proposed EP-based(emerging pattern-based) classification technique using multi-parametric diagnosis indexes. We analyzed linear/nonlinear features of HRV for three recumbent postures and extracted four diagnosis indexes from ST-segments to apply the multi-parametric diagnosis indexes. In this paper, classification model using essential emerging patterns for diagnosing disease was applied. This classification technique discovers disease patterns of patient group and these emerging patterns are frequent in patients with cardiovascular disease but are not frequent in the normal group. To evaluate proposed classification algorithm, 120 patients with AP (angina pectrois), 13 patients with ACS(acute coronary syndrome) and 128 normal people data were used. As a result of classification, when multi-parametric indexes were used, the percent accuracy in classifying three groups was turned out to be about 88.3.


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Cite this article
[IEEE Style]
H. G. Lee, K. Y. Noh, K. H. Ryu, D. Y. Jung, "Multi-parametric Diagnosis Indexes and Emerging Pattern based Classification Technique for Diagnosing Cardiovascular Disease," The KIPS Transactions:PartD, vol. 16, no. 1, pp. 11-26, 2009. DOI: 10.3745/KIPSTD.2009.16.1.11.

[ACM Style]
Heon Gyu Lee, Ki Yong Noh, Keun Ho Ryu, and Doo Young Jung. 2009. Multi-parametric Diagnosis Indexes and Emerging Pattern based Classification Technique for Diagnosing Cardiovascular Disease. The KIPS Transactions:PartD, 16, 1, (2009), 11-26. DOI: 10.3745/KIPSTD.2009.16.1.11.