Mathematical models for predicting and early diagnosis of diseases caused by electromagnetic fields of low-frequency radio frequency range

The paper proposes mathematical models for predicting and diagnosing diseases provoked by exposure to electromagnetic fields of the radio frequency range, which make it possible to control the current state of a person in order to make further decisions about possible correction of body functions, if necessary. Given the incomplete and fuzzy description of the studied class of diseases, soft computing technology was chosen as the basic mathematical apparatus, and, in particular, the synthesis methodology of hybrid fuzzy decision rules, which has proven itself in solving problems with a similar data structure and type of uncertainty. The selected synthesis method allows us to take into account the multiplicative effect of exposure to the human body of electromagnetic fields (EMF) of various modality and intensity, taking into account other endogenous and exogenous risk factors. For powerful and stable EMFs, it is proposed to use a modification of well-known models obtained for industrial power grids. To assess the effect of low-intensity, unstable electromagnetic fields of the radio frequency range on the human body, it is proposed to use fuzzy tabular models and a number of indicators sensitive to the action of the electromagnetic field of the radio frequency range. Such indicators include the state of attention, memory, thinking, as well as the dynamics of changes in the energy state of biologically active points associated with the pathology under study. On the example of electric train drivers, mathematical models for predicting and early diagnosis of the appearance and development of diseases of the nervous system are obtained. It is shown that if additional information about the health status of the subjects is used with electromagnetic risk factors, then confidence in the correct prognosis reaches 0.85, and in the presence of early stages of diseases of the nervous system - 0.95.

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