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Journal of Biomedical Engineering ; (6): 284-287, 2004.
Artigo em Chinês | WPRIM | ID: wpr-291129

RESUMO

Neural networks can fit any nonlinear function. After drawing out several characteristic parameters from the three-dimension spectrum for high frequency QRS waves, we input them into the network and trained the network. In this way, we can get a m-dimension curved surface in the m-dimension space which is constructed by those parameters, and this curved surface divides the space into two parts: the unhealthiness and the health. Now, the network can automatically distinguish between the healthiness and the unhealthiness according to their three-dimension spectrum for high frequency QRS waves.


Assuntos
Humanos , Algoritmos , Doença das Coronárias , Diagnóstico , Eletrocardiografia , Processamento de Imagem Assistida por Computador , Redes Neurais de Computação
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