  In this paper we investigate some stochastic models for tumor-immune systems.
To describe these models, we used a Wiener process, as the noise has a
stabilization effect. Their dynamics are studied in terms of stochastic
stability in the equilibrium points, by constructing the Lyapunov exponent,
depending on the parameters that describe the model. Stochastic stability was
also proved by constructing a Lyapunov function. We have studied and and
analyzed a Kuznetsov-Taylor like stochastic model and a Bell stochastic model
for tumor-immune systems. These stochastic models are studied from stability
point of view and they were represented using the second Euler scheme and Maple
12 software.
