Medicine and the Chaos Theory in Description of Individual and Particular

The article presents three approaches (deterministic, stochastic and chaotic – self-organizing) for studying biomedical systems. The authors show that complex biosystems cann’t be described by deterministic and stochastics because of constant changing parameters xi of a state vector of such systems x=x(t). The fundamental distinguish of deterministic and stochastic systems from chaotic – self-organizing is continuous movement x(t) in phase space of states. The authors also present complex of objects which the authors have been studying for the last 30 years and which conform the type III systems. The particular features of the personalized medicine are presented, that denies possibility of identification of body state at one measurement (a point in a phase space). It is connected with the fact that there is a uniform distribution x(t) in time-domain xi which is revealed in continuous change of distribution functions f(x) for different discrete recording time-domain x(t) at all xi. The authors assert that behavior dynamics of neural networks is similar to work of neuroemulators that is terminated by certainty in quasi-attractor’s volumes.