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Modeling breast tumor growth by a randomized logistic model: A computational approach to treat uncertainties via probability densities

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Modeling breast tumor growth by a randomized logistic model: A computational approach to treat uncertainties via probability densities

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Burgos-Simón, C.; Cortés, J.; Martínez-Rodríguez, D.; Villanueva Micó, RJ. (2020). Modeling breast tumor growth by a randomized logistic model: A computational approach to treat uncertainties via probability densities. European Physical Journal Plus. 135(10):1-14. https://doi.org/10.1140/epjp/s13360-020-00853-3

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/161047

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Title: Modeling breast tumor growth by a randomized logistic model: A computational approach to treat uncertainties via probability densities
Author: Burgos-Simón, Clara Cortés, J.-C. Martínez-Rodríguez, David Villanueva Micó, Rafael Jacinto
UPV Unit: Universitat Politècnica de València. Departamento de Matemática Aplicada - Departament de Matemàtica Aplicada
Universitat Politècnica de València. Instituto Universitario de Matemática Multidisciplinar - Institut Universitari de Matemàtica Multidisciplinària
Issued date:
Embargo end date: 2021-10-14
Abstract:
[EN] We consider a randomized discrete logistic equation to describe the dynamics of breast tumor volume. We propose a method, that takes advantage of the principle of maximum entropy, to assign reliable distributions ...[+]
Subjects: Maximum entropy principle , Computational model fitting , Volume tumor growth , Uncertainty treatment
Copyrigths: Embargado
Source:
European Physical Journal Plus. (eissn: 2190-5444 )
DOI: 10.1140/epjp/s13360-020-00853-3
Publisher:
Springer
Publisher version: https://www.doi.org/10.1140/epjp/s13360-020-00853-3
Project ID:
MINECO/RTI2018-095180-B-I00
AEI/MTM2017-89664-P-AR
Thanks:
This work has been supported by the Spanish Ministerio de Economia, Industria y Competitividad (MINECO), the Agencia Estatal de Investigacion (AEI), and Fondo Europeo de Desarrollo Regional (FEDER UE) Grants MTM2017-89664-P ...[+]
Type: Artículo

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