Classification of acute myocardial ischemia by artificial neural network using echocardiographic strain waveforms.
Comput Biol Med
; 38(4): 416-24, 2008 Apr.
Article
em En
| MEDLINE
| ID: mdl-18321478
ABSTRACT
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, 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.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Sistemas Inteligentes
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Processamento de Imagem Assistida por Computador
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Ecocardiografia
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Diagnóstico por Computador
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Redes Neurais de Computação
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Isquemia Miocárdica
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Eletrocardiografia
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Contração Miocárdica
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Infarto do Miocárdio
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
Limite:
Animals
Idioma:
En
Ano de publicação:
2008
Tipo de documento:
Article