Optimization for Parameter Estimation in Mathematical Model to Predict the Behaviour of Immune System

Abstract

This paper surveys and compares various optimization functions related to diabetes to study the various parameter affecting on diabetes. The most important stage in improving the precision and predictive ability of mathematical models is parameter estimation. Mathematical models for immunity are used to describe and predict the behaviour of the immune system in response to infections, vaccinations, and various other immunological processes. These models are quite complex, involved differential equations and various parameters. Ongoing research aims to better understand these immune-related conditions and develop targeted treatments to modulate immune responses appropriately related to diabetes disease.