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Traditional cardiac auscultation involves a great deal of interpretive skill. Neural networks were trained as phonocardiographic classifiers to determine their viability in this role. All networks had three layers and were trained by backpropagation using only the heart sound amplitude envelope as input. The main aspect of the study was to determine what topologies, gain and momentum factors lead...
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