Automated map of reproductive losses in the Far North region of Russia

Abstract

Objective: to compile an automated map of reproductive losses in the Far North regions of Russia. Material and methods: This article includes statistical analysis of the prevalence and structure of reproductive losses according to the worldwide, Russian, and regional statistics. After describing the general structure of a neural network with a radial basis and a model of a radial neuron, we proceeded to characterization of the error backpropagation algorithm. Hence, our study was based on the normal deviation function. Results. The article substantiates the problem of reproductive losses of the Russian population. On the basis of statistical data, the listing of a neural network program for an interactive map of reproductive losses in the Far North regions of the Russian Federation was built. The obtained data made it possible to identify risk zones in the region. Comparison of indicators for 2000 and 2022 helped revealing the dynamics of change and reporting valid information on the overall increase in the risk of reproductive losses in the region by 17%. Conclusion. We proposed to conduct monitoring of reproductive loss indicators in the regions of the Russian Federation on the basis of a neural information map construction. The compiled map is an interactive map with an assessment of reproductive loss dynamics over the years.