Title
Usage of a novel, similarity-based weighting method to diagnose atherosclerosis from carotid artery Doppler signals.
Abstract
In this paper, we have proposed a novel similarity-based weighting method (SBWM), which combines similarity measure and weighting based on trend association (WBTA) method proposed by Sun Yi et al. (ICNN&B international conference, vol 1, pp 266-269, 2005). The aim of this study is to improve the classification accuracy of atherosclerosis, which is a common disease among the public. The proposed method consists of three parts: (1) feature extraction part related with atherosclerosis disease using fast Fourier transformation (FFT) modeling and calculation of maximum frequency envelope of sonograms, (2) data pre-processing part using SBWM, including different similarity measures such as cosine amplitude method, max-min method, absolute exponential method, and exponential similarity coefficient, and (3) classification part using artificial immune recognition system (AIRS) and Fuzzy-AIRS classifier algorithms. While AIRS and Fuzzy-AIRS algorithms obtained 71.92 and 78.94% success rates, respectively, the combination of SBWM with classifier algorithms including AIRS and Fuzzy-AIRS obtained 100% success rate on all the similarity measures. These results show that SBWM has produced very promising results in the classification of atherosclerosis from carotid artery Doppler signals. In future, we will use a larger dataset to test the proposed method.
Year
DOI
Venue
2008
10.1007/s11517-007-0279-6
Med. Biol. Engineering and Computing
Keywords
Field
DocType
novel similarity-based weighting method � atherosclerosiscarotid artery � fast fourier transformationwelchairsfuzzy-airs � hybrid systems,feature extraction,fast fourier transform,hybrid system
Data mining,Weighting,Similarity measure,Artificial intelligence,Classifier (linguistics),Doppler effect,Computer vision,Trigonometric functions,Exponential function,Pattern recognition,Feature extraction,Fast Fourier transform,Mathematics
Journal
Volume
Issue
ISSN
46
4
0140-0118
Citations 
PageRank 
References 
4
0.44
9
Authors
4
Name
Order
Citations
PageRank
Kemal Polat1134897.38
Fatma Latifoğlu2677.16
Sadık Kara3768.83
Salih Güneş4126778.53