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dc.contributor.authorCosta, José Mir Justino da-
dc.contributor.authorOrlande, Hélcio Rangel Barreto-
dc.contributor.authorCampos Velho, Haroldo Fraga de-
dc.contributor.authorPinho, Suani Tavares Rubim de-
dc.contributor.authorDulikravich, George S.-
dc.contributor.authorCotta, Renato Machado-
dc.contributor.authorCunha Neto, Sílvio Henriques da-
dc.date.accessioned2019-06-14T15:40:04Z-
dc.date.available2023-12-21T03:06:00Z-
dc.date.issued2015-07-10-
dc.identifier.issn1066-5277pt_BR
dc.identifier.urihttp://hdl.handle.net/11422/8469-
dc.description.abstractCancer is characterized by the uncontrolled growth of cells with the ability of invading local organs and/or tissues and of spreading to other sites. Several kinds of mathematical models have been proposed in the literature, involving different levels of refinement, for the evolution of tumors and their interactions with chemotherapy drugs. In this article, we present the solution of a state estimation problem for tumor size evolution. A system of nonlinear ordinary differential equations is used as the state evolution model, which involves as state variables the numbers of tumor, normal and angiogenic cells, as well as the masses of the chemotherapy and anti-angiogenic drugs in the body. Measurements of the numbers of tumor and normal cells are considered available for the inverse analysis. Parameters appearing in the formulation of the state evolution model are treated as Gaussian random variables and their uncertainties are taken into account in the estimation of the state variables, by using an algorithm based on the auxiliary sampling importance resampling particle filter. Test cases are examined in the article dealing with a chemotherapy protocol for pancreatic cancer.en
dc.languageengpt_BR
dc.publisherMary Ann Lieberten
dc.relation.ispartofJournal of Computational Biologyen
dc.rightsAcesso Abertopt_BR
dc.subjectCancer modelingen
dc.subjectInverse problemen
dc.subjectParticle filteren
dc.subjectState estimation problemen
dc.subjectTumor sizeen
dc.titleEstimation of Tumor Size Evolution Using Particle Filtersen
dc.typeArtigopt_BR
dc.identifier.doi10.1089/cmb.2014.0003pt_BR
dc.description.resumoIndisponível.pt_BR
dc.publisher.countryBrasilpt_BR
dc.publisher.departmentNúcleo Interdisciplinar de Dinâmica dos Fluidospt_BR
dc.subject.cnpqCNPQ::CIENCIAS EXATAS E DA TERRA::FISICA::AREAS CLASSICAS DE FENOMENOLOGIA E SUAS APLICACOES::DINAMICA DOS FLUIDOSpt_BR
dc.citation.volume22pt_BR
dc.citation.issue7pt_BR
dc.citation.spage649pt_BR
dc.citation.epage665pt_BR
dc.embargo.terms365 diaspt_BR
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