Usage of a novel, similarity-based weighting method to diagnose atherosclerosis from carotid artery Doppler signals.
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 cla...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 46; no. 4; pp. 353 - 363 |
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| Autores principales: | , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Springer Nature
Apr2008
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=105747491&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 105747491 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Apr2008 vid: 46 iid: 4 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 105747491 NLM17960442 2009936586 10.1007/s11517-007-0279-6 NLM17960442 105747491 ppf: 353 ppct: 10 formats: fmt: @attributes: type: P tig: atl: Usage of a novel, similarity-based weighting method to diagnose atherosclerosis from carotid artery Doppler signals. aug: au: Polat K Latifoglu F Kara S Günes S Polat, Kemal Latifoğlu, Fatma Kara, Sadik Güneş, Salih affil: Department of Electrical and Electronics Engineering, Selcuk University, 42075 Konya, Turkey sug: subj: Carotid Arteries Ultrasonography Carotid Artery Diseases Ultrasonography Information Science Models, Biological Ultrasonography, Doppler Adult Aged Case Control Studies Female Logic Male Mathematics Middle Age Human Adult: 19-44 years Aged: 65+ years Middle Aged: 45-64 years Female Male ab: 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. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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