Classification of acute myocardial ischemia by artificial neural network using echocardiographic strain waveforms

被引：5

作者：

McMahon, Eileen M. ^{[1
]}

Korinek, Josef ^{[2
]}

Yoshifuku, Shiro ^{[2
]}

Sengupta, Partho P. ^{[1
]}

Manduca, Armando ^{[2
]}

Belohlavek, Marek ^{[1
]}

机构：

[1] Mayo Clin, Coll Med, Scottsdale, AZ 85259 USA

[2] Mayo Clin, Coll Med, Rochester, MN 55905 USA

来源：

COMPUTERS IN BIOLOGY AND MEDICINE | 2008年 / 38卷 / 04期

基金：

美国国家卫生研究院;

关键词：

strain echocardiography; artificial neural network; acute myocardial ischemia;

D O I：

10.1016/j.compbiomed.2008.01.003

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

Echocardiographic strain waveforms are highly variable, so their interpretation is experience-dependent and subjective. We tested whether an artificial neural network (ANN) can distinguish between strain waveforms obtained at baseline and during experimentally induced acute ischemia. An open-chest model of coronary occlusion and acute ischemia was used in 14 adult pigs. Strain waveforms were obtained using a GE Vivid 7 ultrasound system. An ANN design was implemented in MATLAB (R), and backpropagation and "leave-one-out" processes were used to train and test it. Specificity of 86% and sensitivity of 87% suggest that ANNs could aid in diagnostic prescreening of echocardiographic strain waveforms. (c) 2008 Elsevier Ltd. All rights reserved.

引用

页码：416 / 424

页数：9

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