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Population Health Assessment Based on Entropy Modeling of Multidimensional Stochastic Systems

  • Alexander N. Tyrsin
  • Garnik G. GevorgyanEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 794)

Abstract

The article attempts to demonstrate the possible application opportunities of multidimensional stochastic systems entropy modeling in medicine on a specific example. An assessment of rural male population health state has been done by the criteria of “healthy”, “practically healthy”, and “diseased”. The entropy levels are determined for the parameters, characterizing the main risk factors for chronic non-communicable diseases, depending on the health group. For each group a single parameter with the largest contribution to the entropy of the population is highlighted, and the dependence degree of this parameter from the others is determined. It was concluded that with the deterioration of health state the population entropy increases. This growth is caused by the increase of randomness entropy. It is shown that with the help of the entropy model it was possible to quite confidently study population health simultaneously by several risk factors. This allows us to count on the successful application of the proposed approach in medicine, as well as in other spheres.

Keywords

Entropy Model Multidimensional random variable Variance Coefficient of determination Risk factor Population Health state 

Notes

Acknowledgments

The reported study was supported by the Russian Foundation for Basic Research (project No. 17-01-00315).

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Ural Federal UniversityYekaterinburgRussia
  2. 2.Scientific and Engineering Center Reliability and Resource of Large Systems and Machine of UB RASYekaterinburgRussia

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