Error evaluation and stability analysis of numerical schemes in multiple sclerosis modeling

This study presents a mathematical model for Multiple Sclerosis (MS) analyzed using the finite difference method and the fourth-order Runge-Kutta (RK4) method. A comparative error analysis shows strong agreement between both methods, with the finite difference approach closely aligning with RK4, as indicated by low Mean Squared Error (MSE), Mean Absolute Error (MAE), and maximum absolute error values. While RK4 provides superior accuracy and stability for long-term simulations, the finite difference method remains a practical and computationally efficient alternative. These findings underscore the potential of mathematical modeling combined with numerical techniques to enhance the understanding of MS dynamics and support the development of optimized intervention strategies. Future research will concentrate on refining the model through the integration of additional biological parameters and clinical data to improve its predictive accuracy.