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Comparative accuracy of neural network models for diagnosing latent arterial hypertension on the basis of data on daily blood pressure monitoring

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Abstract

Daily blood pressure monitoring was performed in 34 apparently healthy subjects and 72 patients with arterial hypertension (AH). We compared the efficiency of diagnosis of latent AH using models based on artificial neural networks of different architecture.

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Authors and Affiliations

  1. State Research Center for Preventive Medicine, Ministry of Health of the Russian Federation, Moscow, Russia

    V. G. Vilkov, R. G. Oganov & S. A. Shal’nova

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  1. V. G. Vilkov
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  2. R. G. Oganov
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  3. S. A. Shal’nova
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Additional information

Original Russian Text © V.G. Vilkov, R.G. Oganov, S.A. Shal’nova, 2006, published in Fiziologiya Cheloveka, 2006, Vol. 32, No. 6, pp. 33–37.

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Vilkov, V.G., Oganov, R.G. & Shal’nova, S.A. Comparative accuracy of neural network models for diagnosing latent arterial hypertension on the basis of data on daily blood pressure monitoring. Hum Physiol 32, 657–661 (2006). https://doi.org/10.1134/S0362119706060053

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  • DOI: https://doi.org/10.1134/S0362119706060053

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