E.I. Denisov - Dr.Sc. (Biol.), Ph.D. (Eng.), Professor, Research Institute of Occupational Health under the Russian Academy of Sciences (FSBI «RIOH» RAS) (Moscow). E-mail: denisov28@yandex.ru V.F. Pfaf - Ph.D. (Med.), Director of NUZ \"Scientific Clinical Center of JSC\" Russian Railways \"(Moscow). E-mail:nkcrzd@gmail.com I.V. Stepanian - Dr.Sc. (Biol.), Ph.D. (Eng.), Leading Research Scientist, Laboratory of biodynamics, Institute for Machine Science named by A.A. Blagonravov of the RAS, Leading Research Scientist, Moscow State Сonservatory named by P.I. Chaikovsky (Moscow). E-mail: neurocomp.pro@gmail.com C.G. Gorokhova - Dr.Sc. (Med.), Professor, Head Laboratory of Experimental Cardiology, NUZ \"Scientific Clinical Center of JSC\" Russian Railways \"(Moscow). E-mail: cafedra2004@mail.ru

Institute of occupational health, Research Clinical center of Russian Railways, Institute of Machines Science named after A.A.Blagonravov of the Russian Academy of Sciences The concept of allostasis as a model of predictive regulation and allostatic load (AL) as an integrated clinical measure of the influence of stress factors are discussed. The evolution of ideas of homeostasis and allostasis in publications are sum-marized. The emergence of a synthesis of work on biomarkers, methods of determining of ALs and their assessment for dif-ferent groups of workers are noted. Russian authors support and have been developing this concept. The example of allostatic neural network model is a model of autonomous adaptive control (AAC) by A.A. Zhdanov. Systemic effect of teaching and learning is achieved through a biologically inspired model of the digital neuron. The algorithm for the calculation of the AN index and its computer implementation for storing data for the purpose of verification of the concept of allostasis and monitoring the health of workers in occupations with high stress and responsibility. This work was financially supported partically by RHSF in grant № 15-03-00519а «Post-non-classic paradigm of artificial intellect». This work was financially supported by RFH in grant № 15-03-00519а «Post-non-classic paradigm of artificial intellect».

 

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