A fuzzy mathematical model for tumor growth pattern using generalized Hukuhara derivative and its numerical analysis

Fuzzy mathematical modeling has been extensively used in recent years as a helpful tool to achieve a stronger and broader understanding of a specific biological topic such as cancer. The Fuzzy mathematical model allows one to analyze the structure both qualitatively and quantitatively using mathematical methods and clarifies a tool for observing the results of different components and making behavioral projection. To reduce the ambiguity of model parameters, a fuzzy environment has been designed to address a more accurate mathematical tumor growth model. The complete pattern of tumor growth mechanism is captured with the fuzzy mathematical model using fuzzy differential equation. The concept of Generalized Hukuhara derivative is used to transform the differential equation into a system of two ordinary differential equations. The numerical simulation has also been given to support the mathematical tumor growth model in a fuzzy environment. • The exponential, logistic, and Gompertz model in tumor growth is formulated under fuzzy environment. • The coefficient, initial condition, and both of the models are taken as fuzzy numbers. • The generalized Hukuhara differentiability concept which is a powerful method of the derivative is used for analyzing the model. • Numerical simulation using MATLAB software is used to support this work.