title: Pattern detection of atherosclerosis from carotid artery doppler signals using fuzzy weighted pre-processing and Least Square Support Vector Machine (LSSVM).
abstract: Carotid Artery Doppler Signals were recorded from 114 subjects, 60 of whom had Atherosclerosis disease while the rest were healthy controls. Diagnosis of Atherosclerosis from Carotid Artery Doppler Signals was conducted using Fuzzy weighted pre-processing and Least Square Support Vector Machine (LSSVM). First, in order to determine the LSSVM inputs, spectral analysis of Carotid Artery Doppler Signals was performed via Autoregressive (AR) modeling. Then, fuzzy weighted pre-processing based is proposed expert system, applied to inputs obtained from spectral analysis of Carotid Artery Doppler Signals. LSSVM was used to detect Atherosclerosis from Carotid Artery Doppler Signals. All data set were obtained from Carotid Artery Doppler Signals of healthy subjects and subjects suffering from Atherosclerosis disease. The employed expert system has achieved 100% classification accuracy using a 10-fold Cross Validation (CV) method.
authors: Department of Electrical & Electronics Engineering, Selcuk University, 42075, Konya, Turkey.
authors: Kemal
authors: K
authors: Polat
authors: Sadik
authors: S
authors: Kara
authors: Fatma
authors: F
authors: Latifoğlu
authors: Salih
authors: S
authors: Güneş
mesh_terms: D000465:Algorithms; D002340:Carotid Artery Diseases / Q000000981:diagnostic imaging*; D005103:Expert Systems; D017143:Fuzzy Logic; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016018:Least-Squares Analysis; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D018608:Ultrasonography, Doppler / Q000379:methods*