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  • The aim of this study was the differential diagnosis of balance disorders thus a clear distinction between the patient with balance disorders and the patient without balance disorders. The data used in this article was measured under the static conditions on the posturography platform. The patients were split to three groups, peripheral, central and normal based on doctor's diagnosis. These patients were used as input to neural network. Was selected the multilayer network with Backpropagation algorithm. The network was learned the combination of the particular diagnosis thus, the network was learned the combination of normal-peripheral, peripheral-central and central-normal diagnosis. The test set contained 10 normal, 10 peripheral, and 10 central patients, who were evaluated already learned the multilayer neural networks with Backpropagation algorithm. From the results was found out that the proposed multilayer network was able to correctly determine the diagnosis of the particularly patients of 67%.
  • The aim of this study was the differential diagnosis of balance disorders thus a clear distinction between the patient with balance disorders and the patient without balance disorders. The data used in this article was measured under the static conditions on the posturography platform. The patients were split to three groups, peripheral, central and normal based on doctor's diagnosis. These patients were used as input to neural network. Was selected the multilayer network with Backpropagation algorithm. The network was learned the combination of the particular diagnosis thus, the network was learned the combination of normal-peripheral, peripheral-central and central-normal diagnosis. The test set contained 10 normal, 10 peripheral, and 10 central patients, who were evaluated already learned the multilayer neural networks with Backpropagation algorithm. From the results was found out that the proposed multilayer network was able to correctly determine the diagnosis of the particularly patients of 67%. (en)
Title
  • Multilayer neural network in differential diagnosis of balance disorders
  • Multilayer neural network in differential diagnosis of balance disorders (en)
skos:prefLabel
  • Multilayer neural network in differential diagnosis of balance disorders
  • Multilayer neural network in differential diagnosis of balance disorders (en)
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  • RIV/70883521:28140/12:43868543!RIV13-MSM-28140___
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  • 152370
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  • RIV/70883521:28140/12:43868543
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  • posturography, Romberg test, Backpropagation algorithm, differential diagnosis, balance disorders, peripheral, central (en)
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  • [020C8E9E3195]
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  • Proceedings of the 16th WSEAS International Conference on Systems
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  • Dolinay, Viliam
  • Pivničková, Lucie
  • Vašek, Vladimír
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number of pages
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  • WSEAS Press (GR)
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  • 978-1-61804-108-1
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  • 28140
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