Eventos Anais de eventos
COBEM 2017
24th ABCM International Congress of Mechanical Engineering
Bayesian Approach to Parameter Estimation and Selection of Growth Models of Tumor Cells
Submission Author:
ADRIANA MACHADO MALAFAIA DA MATA , ES
Co-Authors:
JOSE MIR JUSTINO DA COSTA, Wellington Betencurte da Silva, JULIO CESAR SAMPAIO DUTRA, ADRIANA MACHADO MALAFAIA DA MATA
Presenter: Wellington Betencurte da Silva
doi://10.26678/ABCM.COBEM2017.COB17-0814
Abstract
Cancer is a disease that arises from the disordered growth of cells. Commonly, antineoplastic chemotherapy is used to treat the most common cancers. In this context, researches have turned to mathematical models that describe the growth of tumor cells with an action of a chemotherapeutic drug. Faced with a variety of models, a method for selecting the most suitable model has become promising. This paper studies mathematical models of tumor cell growth and applies the Approximate Bayesian Computation (ABC) method based on the Sequential Monte Carlo (SMC) to select the best model that fits the observed data. A two-compartment pharmacokinetic model allowed the study of orally administered antineoplastic drugs. In addition, ABC SMC was able to estimate the parameters of the selected model.
Keywords
Approximate Bayesian Computation (ABC), Sequential Monte Carlo (SMC), models of cell growth, Bayesian model selection.
