title: Medical application of artificial immune recognition system (AIRS): diagnosis of atherosclerosis from carotid artery Doppler signals.
abstract: This study was conducted to distinguish between atherosclerosis and healthy subjects. Hence, we have employed the maximum envelope of the carotid artery Doppler sonograms derived from Fast Fourier Transformation-Welch method and Artificial Immune Recognition System (AIRS). The fuzzy appearance of the carotid artery Doppler signals makes physicians suspicious about the existence of diseases and sometimes causes false diagnosis. Our technique gets around this problem using AIRS to decide and assist the physician to make the final judgment in confidence. AIRS has reached 99.29% classification accuracy using 10-fold cross validation. Results show that the proposed method classified Doppler signals successfully.
authors.affiliation: Department of Electronics Engineering, Erciyes University, 38039 Kayseri, Turkey. fdirgenali@tse.org.tr
authors.forename: Fatma
authors.initials: F
authors.lastname: Latifoğlu
authors.forename: Halife
authors.initials: H
authors.lastname: Kodaz
authors.forename: Sadik
authors.initials: S
authors.lastname: Kara
authors.forename: Salih
authors.initials: S
authors.lastname: Güneş
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D001185:Artificial Intelligence; D050197:Atherosclerosis / Q000175:diagnosis* / Q000000981:diagnostic imaging*; D002339:Carotid Arteries / Q000000981:diagnostic imaging*; D003936:Diagnosis, Computer-Assisted; D005260:Female; D005583:Fourier Analysis; D006801:Humans; D008297:Male; D008875:Middle Aged; D018608:Ultrasonography, Doppler