Mathematical model of clinical processes implemented in the class of stohastic Markov control processes with memory

The work is devoted to problem of mathematical modeling of the diagnostic and treatment process. There is a whole arsenal of methods designed for the processing of experimental data and building models of dynamic objects (processes). But the problem of mathematical modeling of the diagnostic and treatment process is still not resolved. Difficulties associate with the medicine area itself. The dimensions of control process (medical treatments) and of observable characteristics of the patient state (medical symptoms and indicators) are very big. These dimensions create a barrier for formalization and construction of dynamic model of clinical process based on experimental data. We propose an approach to the construction of abstract mathematical model of clinical process in the class of stochastic Markov processes with memory. The model is based on two postulates. Implementation of model in the class of stochastic processes; according to Ross Ashby’s system classification complex systems and processes should have stochastic nature. Usage of precedents is the next basis of the approach. Medicine is very conservative, active actions (control) are selected on the basis of already known precedents that have been proven effective (evidence based medicine). The conceptual basis of the model has a clear, meaningful interpretation for medical professionals.