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Determining the mathematical dynamics and associated parameter values that should be used to accurately reflect tumor growth continues to be of interest to mathematical modelers, experimentalists and practitioners. However, while there are…

Cell Behavior · Quantitative Biology 2013-12-18 E. A. Sarapata , L. G. de Pillis

Despite advances in methods to interrogate tumor biology, the observational and population-based approach of classical cancer research and clinical oncology does not enable anticipation of tumor outcomes to hasten the discovery of cancer…

A macroscopic model of the tumor Gompertzian growth is proposed. The new approach is based on the energetic balance among the different cell activities, described by methods of statistical mechanics and related to the growth inhibitor…

Cell Behavior · Quantitative Biology 2007-05-23 Paolo Castorina , Dario Zappala'

A macroscopic model of the tumor Gompertzian growth is proposed. This approach is based on the energetic balance among the different cell activities, described by methods of statistical mechanics and related to the growth inhibitor factors.…

Tissues and Organs · Quantitative Biology 2017-08-23 Paolo Castorina , Dario Zappalá

Mathematical modeling in cancer has been growing in popularity and impact since its inception in 1932. The first theoretical mathematical modeling in cancer research was focused on understanding tumor growth laws and has grown to include…

Tissues and Organs · Quantitative Biology 2013-05-22 Jacob G. Scott , Philip Gerlee , David Basanta , Alexander G. Fletcher , Philip K. Maini , Alexander RA Anderson

We propose a new model of cancer growth based on nonextensive entropy. The evolution equation depends on the nonextensive parameter q. The exponential, the logistic, and the Gompertz growth laws are particular cases of the generalized…

Medical Physics · Physics 2009-11-11 Jorge A. González , Irving Rondón

During the last decades, medical observations and multiscale data concerning tumor growth are mounting. At the same time, contemporary imaging techniques well established in clinical practice, provide a variety of information on real-time,…

Tissues and Organs · Quantitative Biology 2017-12-11 Markos Antonopoulos , Georgios Stamatakos

In this article we shall trace the historical development of tumour growth laws, which in a quantitative fashion describe the increase in tumour mass/volume over time. These models are usually formulated in terms of differential equations…

Tissues and Organs · Quantitative Biology 2013-02-11 P. Gerlee

Strong experimental evidence has indicated that tumor growth belongs to the molecular beam epitaxy universality class. This type of growth is characterized by the constraint of cell proliferation to the tumor border, and surface diffusion…

Quantitative Methods · Quantitative Biology 2009-11-13 Carlos Escudero

As biomedical sciences discover new layers of complexity in the mechanisms of life and disease, mathematical models trying to catch up with these developments become mathematically intractable. As a result, in the grand scheme of things,…

Quantitative Methods · Quantitative Biology 2019-06-06 Leonid Hanin

In this paper we propose a systematic approach to construct mathematical models describing populations of cancer-cells at different stages of disease development. The methodology we propose is based on stochastic Concurrent Constraint…

Computational Engineering, Finance, and Science · Computer Science 2011-09-08 Luca Bortolussi , Alberto Policriti

Mathematical models (MMs) are a powerful tool to help us understand and predict the dynamics of tumour growth under various conditions. In this work, we use 5 MMs with an increasing number of parameters to explore how certain (often…

Quantitative Methods · Quantitative Biology 2024-08-16 Jamie Porthiyas , Daniel Nussey , Catherine A. A. Beauchemin , Donald C. Warren , Christian Quirouette , Kathleen P. Wilkie

We propose a model for describing the growth on an untreated tumor, which is characterized in a simple way by a minimal number of parameters with a well-defined physical interpretation. The model is motivated by invoking the Master Equation…

Populations and Evolution · Quantitative Biology 2007-05-23 José F. Nieves , Marcelo R. Ubriaco

Tumor growth has long been a target of investigation within the context of mathematical and computer modelling. The objective of this study is to propose and analyze a two-dimensional probabilistic cellular automata model to describe…

Tissues and Organs · Quantitative Biology 2009-11-13 E. A. Reis , L. B. L. Santos , S. T. R. Pinho

Forecasting tumor growth is critical for optimizing treatment. Classical growth models such as the Gompertz and Bertalanffy equations capture general tumor dynamics but may fail to adapt to patient-specific variability, particularly with…

Machine Learning · Computer Science 2025-12-01 Kavya Subramanian , Prathamesh Dinesh Joshi , Raj Abhijit Dandekar , Rajat Dandekar , Sreedath Panat

Cancer pathology is unique to a given individual, and developing personalized diagnostic and treatment protocols are a primary concern. Mathematical modeling and simulation is a promising approach to personalized cancer medicine. Yet, the…

Tissues and Organs · Quantitative Biology 2020-08-03 Alvaro Köhn-Luque , Xiaoran Lai , Arnoldo Frigessi

Longitudinal tumour volume data from head-and-neck cancer patients show that tumours of comparable pre-treatment size and stage may respond very differently to the same radiotherapy fractionation protocol. Mathematical models are often…

Tumor growth has a number of features in common with a physical process known as molecular beam epitaxy. Both growth processes are characterized by the constraint of growth development to the body border, and surface diffusion of…

Quantitative Methods · Quantitative Biology 2009-11-13 Carlos Escudero

The work presents a study of the non-linear mathematical model of tumor growth, proposed by Kolev and Zubik-Kowal (2011). The model is described by a system composed of four partial differential equations that represent the evolution of the…

Tissues and Organs · Quantitative Biology 2025-06-02 Jesika Maganin , Neyva Maria Lopes Romeiro , Eliandro Rodrigues Cirilo , Paulo Laerte Natti

This work studies lung tumor growth prediction from sparse and irregular longitudinal computed tomography (CT) observations with measurement variability. A Bayesian physics-informed neural network is developed by combining Gompertz growth…

Machine Learning · Computer Science 2026-05-14 Lingfei Kong , Haoran Ma
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