Dynamical Analysis of Generalized Tumor Model with Caputo Fractional-Order Derivative

• Published in: Fractal and fractional Vol. 7; no. 3; p. 258
• Main Authors: Padder, Ausif, Almutairi, Laila, Qureshi, Sania, Soomro, Amanullah, Afroz, Afroz, Hincal, Evren, Tassaddiq, Asifa
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.03.2023
• Subjects: Artificial intelligence; B cells; Biological models (mathematics); Calculus; Caputo fractional derivative; Comparative analysis; Curve fitting; Epidemics; Epidemiology; Fractional calculus; Growth models; Immune system; Infectious diseases; Lung cancer; Lymphocytes; Mathematical models; Medical research; Medicine, Experimental; Numerical analysis; numerical simulation; Order parameters; parameter fitting; Public health; Radiation therapy; Stability analysis; Tumors; tumor–immune interaction
• ISSN: 2504-3110; 2504-3110
• DOI: 10.3390/fractalfract7030258

In this study, we perform a dynamical analysis of a generalized tumor model using the Caputo fractional-order derivative. Tumor growth models are widely used in biomedical research to understand the dynamics of tumor development and to evaluate potential treatments. The Caputo fractional-order derivative is a mathematical tool that is recently being applied to model biological systems, including tumor growth. We present a detailed mathematical analysis of the generalized tumor model with the Caputo fractional-order derivative and examine its dynamical behavior. Our results show that the Caputo fractional-order derivative provides a more accurate description of the tumor growth dynamics compared to classical integer-order derivatives. We also provide a comprehensive stability analysis of the tumor model and show that the fractional-order derivative allows for a more nuanced understanding of the stability of the system. The least-square curve fitting method fits several biological parameters, including the fractional-order parameter α. In conclusion, our study provides new insights into the dynamics of tumor growth and highlights the potential of the Caputo fractional-order derivative as a valuable tool in biomedical research. The results of this study shell have significant implications for the development of more effective treatments for tumor growth and the design of more accurate mathematical models of tumor development.