Aspect's work has shown that quantum objects have complete uncertainty in the predictions of their future. Likewise, living systems (systems of the third type according to Weaver's classification) also demonstrate a lack of predictability of the future. This has been proven on many models of the Eskov-Zinchenko effect, where for all living systems there is a similar uncertainty. This uncertainty poses new challenges for modern science and requires the creation of a new science that can describe the special properties of such systems. This new science must be different from modern deterministic and stochastic science, which cannot cope with the lack of predictability of the future.

A number of Nobel Prize winners (M. Gell-Mann, I. R. Prigogine, R. Penrose, V. L. Ginzburg) have repeatedly expressed their belief in the existence of dynamical chaos in the study of the dynamics of the behavior of biosystems. However, 20 years ago, the Eskov-Zinchenko effect was proved, when successively obtained samples of human movement parameters demonstrate the absence of statistical stability. A natural question arises regarding the stability of Lorenz dynamical chaos in the behavior of biosystems. In the paper, the main three criteria of dynamical chaos are presented, which are not met by the parameters of the cardio intervals. In the article, the absence of such chaos in the heart performance has been proved.

The founder of thermodynamics of nonequilibrium systems, I.R. Prigogine, and a number of other Nobel prize winners (M. Gell-Mann, V.L. Ginzburg, R. Penrose) have repeatedly expressed their opinion about the reality of dynamic chaos in biosystems. However, the identification and proof of the global statistical instability of any samples of any parameters of the human body (in the form of the Eskov-Zinchenko effect) casts doubt on such statements. The article presents three main criteria for identifying dynamic chaos. It is shown that none of these criteria can prove this chaos in biosystems (both in normal and pathological conditions).

At the beginning of the 21st century, the Eskov-Zinchenko effect was proved as the sample's uniqueness of any of the human body functions' parameter. Such statistical uncertainty completes the further use of statistics in medicine. Moreover, theway to find the main diagnostic signs (order parameters) inmedicine is not known now. In this regard, it is supposed to use an artificial neural network to distinguish between samples and find order parameters. The article presents a typical example of solving such a problem in dermatology by the diagnosis of actinic dermatitis.

The first quarter of the 21st century is coming to an end, but the problem of reduction has not become the central problem of the 21st century, as Nobel laureate V.L. Ginzburg. At the end of the 20th century, he identified three “great” problems of physics and all of science, and they are discussed today in the framework of the new theory of chaos-self-organization, the foundations of which we now present. These great problems led to the uniqueness of the samples, the loss of homogeneity of any groups, and the appearance of type 1 uncertainty (statistics do not work). We have proved the reality of these three “great” problems experimentally. #CSOC1120.

The effect of industrial factors on the human body is very often very difficult to identify within the framework of existing statistical methods. This is especially true for identifying the effects of weak industrial electromagnetic fields on the work of the heart. This factor can last for decades, and new computational methods and new mathematical theories are needed to reveal the effects. This work demonstrates a new approach based on neural network technologies, which makes it possible to identify such effects in different groups of subjects. In this case, new (special) modes of operation of artificial neural networks are used. As a result, not only groups of subjects are divided, but also the main diagnostic signs are found, which in the system synthesis are designated as order parameters.

In the 90s, the Nobel laureate Ilya Romanovich Prigogine wrote and published his last monograph, The End of Certainty: Time, Chaos, and the New Laws of Nature. The scientist completed the further use of deterministic science in the study of non-equilibrium biosystems in this book. However, in the middle of the 20th century Weaver and Bernstein proposed to take biosystems beyond the limits of all deterministic and stochastic science. The predictions of these two scientists got their realization at the beginning of the 21st century in connection with the creation of chaos-self-organization theory and the discovery of the Eskov-Zinchenko effect. Now it becomes obvious that it is necessary to create the third science of biosystems with uncertainties of the 1st and 2nd types and the heuristic work of artificial neural networks.

The possibilities of applying models, methods and laws of physics to the study of biosystems have been repeatedly discussed by various prominent physicists of the 20th century. Six Nobel laureates were convinced of physics reduction to biosystems (E. Schrodinger, A.V. Hill, I.R. Prigogine, M. Gell-Mann, R. Penrose, and V.L. Ginzburg). However, the reality turned out to be different. W. Weaver was right, when denied the reduction of all deterministic and stochastic science to biosystems. The question remained about the possibilities of dynamic chaos in the description of biosystems. The article shows that this is also impossible. Biosystems do not generate dynamic Lorentz chaos; they demonstrate a sharp change in the highest Lyapunov exponent λi and the intersection of phase trajectories in the phase space of states.

The data on the identification of differences in the reactions of the human cardiovascular system in the North of the Russian Federation in response to the action of industrial electromagnetic fields are presented. The reactions of female male organisms depending on the influence of the studied fields and age-related changes have been established.