Volume 19, Issue 4

In this paper we consider models of learning diagnostics by precedents using pattern recognition methods and adjustment of layered neural nets. We show that in this case the problem reduces to the construction of committee constructions generalizing the notion of the solution to the system of linear inequalities. The methods proposed are justified. These methods are applied to the problems of medical diagnostics and for modelling empirical regularities.

In this paper we consider models of learning diagnostics by precedents using pattern recognition methods and adjustment of layered neural nets. We show that in this case the problem reduces to the construction of committee constructions generalizing the notion of the solution to the system of linear inequalities. The methods proposed are justified. These methods are applied to the problems of medical diagnostics and for modelling empirical regularities.

The aim of this paper was to construct the mathematical model of the kinetics of nonhemagglutinating mutant accumulation in the cloned population of hemagglutinating echovirus 11 and to verify the model adequacy by comparing the results of biological and numerical experiments.

The aim of this paper was to construct the mathematical model of the kinetics of nonhemagglutinating mutant accumulation in the cloned population of hemagglutinating echovirus 11 and to verify the model adequacy by comparing the results of biological and numerical experiments.

This paper is devoted to the construction of the mathematical model of the tuberculosis morbidity dynamics. The model takes into account the peculiarities of morbidity epidemiology and its control. The model is adjusted to the data collected in the Orlovskaya oblast. The results obtained will be used for the analysis of the epidemiological situation and designing the effective strategy of tuberculosis control.

This paper is devoted to the construction of the mathematical model of the tuberculosis morbidity dynamics. The model takes into account the peculiarities of morbidity epidemiology and its control. The model is adjusted to the data collected in the Orlovskaya oblast. The results obtained will be used for the analysis of the epidemiological situation and designing the effective strategy of tuberculosis control.

In this paper, we analyse the structure of equations in the earlier proposed mathematical model of the dynamics of age-related changes in population of peripheral T lymphocytes. To investigate behaviour of the model solutions in a wide range of values of variables we introduce a linear relation between the rate constants of T lymphocytes proliferation and the values of the mean length of telomeric chromosome fragments spent by naive and memory cells in the course of immune response, as well as the dependence of these parameters on the value of the cell replicative potential. We obtain sufficient conditions for existence, uniqueness, and positiveness of solutions over the whole time interval. The results of numerical calculations illustrate the capabilities of the model for describing accelerated aging mechanisms of the immune system using the example of HIV infection.

In this paper, we analyse the structure of equations in the earlier proposed mathematical model of the dynamics of age-related changes in population of peripheral T lymphocytes. To investigate behaviour of the model solutions in a wide range of values of variables we introduce a linear relation between the rate constants of T lymphocytes proliferation and the values of the mean length of telomeric chromosome fragments spent by naive and memory cells in the course of immune response, as well as the dependence of these parameters on the value of the cell replicative potential. We obtain sufficient conditions for existence, uniqueness, and positiveness of solutions over the whole time interval. The results of numerical calculations illustrate the capabilities of the model for describing accelerated aging mechanisms of the immune system using the example of HIV infection.

We earlier developed the mathematical model of electrical and mechanical activity in myocardium, which takes into account both direct coupling and feedback between excitation and contraction. In this paper, in the framework of the model we found conditions under which both the abrupt shortening and stretch of cardiac preparation can cause extra action potentials and hence anomalous deformations can be arrhythmia sources. In the framework of the model, we establish possible mechanisms underlying the Anrep phenomenon that reflects a relationship between myocardium contraction and vascular resistance in the intact heart.

We earlier developed the mathematical model of electrical and mechanical activity in myocardium, which takes into account both direct coupling and feedback between excitation and contraction. In this paper, in the framework of the model we found conditions under which both the abrupt shortening and stretch of cardiac preparation can cause extra action potentials and hence anomalous deformations can be arrhythmia sources. In the framework of the model, we establish possible mechanisms underlying the Anrep phenomenon that reflects a relationship between myocardium contraction and vascular resistance in the intact heart.

This article presents an attempt to connect pathogen's properties that play an essential role on the cellular level with the results of a pathogen's activity observed on the population level. Since a disease develops in an individual, the features of the pathogen and the individual determine a disease course and outcome. Clearly, individual responses to a pathogen strongly affect the spread of a disease in a population. This leads to our approach of basing the construction of our epidemic model on a disease model that describes a disease course in an individual because this model takes into account both the properties of a pathogen and an individual.

This article presents an attempt to connect pathogen's properties that play an essential role on the cellular level with the results of a pathogen's activity observed on the population level. Since a disease develops in an individual, the features of the pathogen and the individual determine a disease course and outcome. Clearly, individual responses to a pathogen strongly affect the spread of a disease in a population. This leads to our approach of basing the construction of our epidemic model on a disease model that describes a disease course in an individual because this model takes into account both the properties of a pathogen and an individual.