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Construction of Teaching Databases for the Neuronetwork Analyzer of Electrocardiography Signals


R.V. Isakov, J.A. Lukyanova

Researches on artificial neuron networks are related to that the method of treatment of information a human brain in a root differs from methods, applied by ordinary digital computers.  Long-term researches, conducted with the most different obvious algorithms, rotined that medical tasks, having non-obvious character, decided obvious methods with accuracy and comfort, quite insufficient for the wide practical use in the concrete tasks of diagnostics, prognostication and making decision.  Procedure, used for the process of teaching, is named a teaching algorithm. This procedure ranges in set procedure sinaptic weight of neuron network for providing of necessary neurons intercommunications structure.  It is possible to offer two basic variants of neuron network organization for the automated analysis of electrocardiography signals.  It is possible to consider architecture the first variant similar with classic description of multi-layered perceptron, and second - modular construction of neuron network, which consists of a few parallel located neuronetwork modules, built on the basis of multi-layered perceptron structure.  As a source of entrance data for the neuronetwork analyzer of electrocardiography signals the single channel recorder of electrocardiogram, productive registration of electrocardiosignal in one of the standard leads, was chosen.  The structures of teaching databases were offered for two variants of organization of neuron network. For filling of the developed databases the open informative system of «PhisioNET» was used.  The created and trained neuron network it is assumed to use jointly with a single channel electrocardiosignals recorder in the domestic systems of the automated analysis of the functional state of the cardiac-vascular system, and also during a mass express-researches for the selection of «risk groups»

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