Problems of time series analysis for short-term and long-term prediction of morbidity using artificial neural networks are discussed. The predictive capacity of simple neural networks (bilayer perceptron) was tested for scarlet fever morbidity. It is demonstrated that neural networks using a special training sample provided satisfactory prognosis. The seasonal dynamics of scarlet fever morbidity was predicted in all test variants. The prognosis error for a two-year period was 40%.
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Translated from Meditsinskaya Tekhnika, Vol. 47, No. 1, Jan.-Feb., 2013, pp. 35-38.
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Dmitriev, A.N., Kotin, V.V. Time Series Prediction of Morbidity Using Artificial Neural Networks. Biomed Eng 47, 43–45 (2013). https://doi.org/10.1007/s10527-013-9331-z
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DOI: https://doi.org/10.1007/s10527-013-9331-z