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- W2146368242 abstract "Artificial Neural Networks (ANN) are computer-based expert systems that have proved to be useful in pattern recognition tasks. ANN can be used in different phases of the decision-making process, from classification to diagnostic procedures. In this work, we develop two methods. The first one based on a compound neural network (CNN) composed of three different multilayer neural networks of the feed forward type, and the second one based on only a multi-layer perceptron (MLP). Such both of them have the capability to classify electrocardiograms (ECG) as normal or as carrying atrioventricular blocks (AVB). These networks were fed with same measurements from one lead of the ECG. A single output unit encodes the probability of AVB occurrences. The difference in performance between the two neural networks classifiers was measured as the difference in area under the receiver operating characteristic curves (ROC). The results show that the CNN and MLP have a good performance in detecting AVBs." @default.
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- W2146368242 date "2008-01-01" @default.
- W2146368242 modified "2023-09-23" @default.
- W2146368242 title "Agreement Between Multi-Layer Perceptron and a Compound Neural Network on ECG Diagnosis of Aatrioventricular Blocks" @default.
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