title: Early detection of coronary artery disease in patients studied with magnetocardiography: an automatic classification system based on signal entropy.
abstract: We propose an automatic system for the classification of coronary artery disease (CAD) based on entropy measures of MCG recordings. Ten patients with coronary artery narrowing ≥ or ≤ 50% were categorized by a multilayer perceptron (MLP) neural network based on Linear Discriminant Analysis (LDA). Best results were obtained with MCG at rest: 99% sensitivity, 97% specificity, 98% accuracy, 96% and 99% positive and negative predictive values for single heartbeats. At patient level, these results correspond to a correct classification of all patients. The classifier's suitability to detect CAD-induced changes on the MCG at rest was validated with surrogate data.
authors.affiliation: Behavioral Imaging and Neural Dynamics Center, G. d'Annunzio University, Via dei Vestini 33, 66013 Chieti, Italy.
authors.forename: Martin
authors.initials: M
authors.lastname: Steinisch
authors.forename: Paul R
authors.initials: PR
authors.lastname: Torke
authors.forename: Jens
authors.initials: J
authors.lastname: Haueisen
authors.forename: Birgit
authors.initials: B
authors.lastname: Hailer
authors.forename: Dietrich
authors.initials: D
authors.lastname: Grönemeyer
authors.forename: Peter
authors.initials: P
authors.lastname: Van Leeuwen
authors.forename: Silvia
authors.initials: S
authors.lastname: Comani
mesh_terms: D000328:Adult; D000368:Aged; D003324:Coronary Artery Disease / Q000145:classification* / Q000175:diagnosis*; D016002:Discriminant Analysis; D042241:Early Diagnosis; D019277:Entropy; D005260:Female; D006801:Humans; D053798:Magnetocardiography / Q000379:methods*; D008297:Male; D008875:Middle Aged; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted