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dc.contributor.authorPérez-García, Víctor M.
dc.contributor.authorFitzpatrick, Susan
dc.contributor.authorPérez-Romasanta, Luis A.
dc.contributor.authorPesic, Milica
dc.contributor.authorSchucht, Philippe
dc.contributor.authorArana, Estanislao
dc.contributor.authorSanchez-Gomez, Pilar 
dc.date.accessioned2020-11-16T20:37:11Z
dc.date.available2020-11-16T20:37:11Z
dc.date.issued2016
dc.identifier.citationApplied Mathematics and Nonlinear Sciences 1(2) (2016) 423–436es_ES
dc.identifier.urihttp://hdl.handle.net/20.500.12105/11349
dc.description.abstractCancer is a major health problem in the industrialized world being the second leading cause of death in the USA and EU after heart disease. A huge quantity of resources is spent every year on cancer research, resulting in a small, yet sustained, reduction in cancer death rates (in the last ten years this was about 1 − 2% per year in the US) [1]. However, there is a widespread concern about the slow pace at which these discoveries in fundamental biology are translated into safe and effective clinical interventions. Statistics is already considered to be a basic ingredient of medical education and routinely used in research, specifically in clinical studies. This is so even when many physicians have a limited understanding of statistics and risk analysis [2]. However, the potential of other mathematical tools such as differential equations, advanced numerical methods, optimization, etc, have not been broadly incorporated into medical research on clinical care. This is so in spite of the fact that these methods are part of the standard toolbox of the applied mathematician that have proven useful in many other fields of science and engineering.es_ES
dc.description.sponsorshipVMP-G is partially supported by Ministerio de Economía y Competitividad/FEDER (MINECO), Spain [grant numbers: MTM2012-31073 and MTM2015-71200-R], Consejería de Educación Cultura y Deporte from Junta de Comunidades de Castilla-La Mancha (Spain) [grant number PEII-2014-031-P] and James S. Mc. Don-nell Foundation (USA) 21st Century Science Initiative in Mathematical and Complex Systems Approaches for Brain Cancer (Special Initiative Collaborative - Planning Grant 220020420 and Collaborative award 220020450). PSG is supported by MINECO under grants RD12/0036/0027 and SAF2015-65175-R. We would like to acknowledge MôLAB members (Universidad de Castilla-La Mancha, Spain) Juan Belmonte-Beitia, Gabriel F. Calvo and Alicia Martínez-González for a critical reading of the manuscript.es_ES
dc.language.isoenges_ES
dc.publisherUP4 Institute of Sciences S.L.es_ES
dc.relation.isversionofPublisher's versiones_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.titleApplied mathematics and nonlinear sciences in the war on canceres_ES
dc.typeArtículoes_ES
dc.rights.licenseAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.format.volume1es_ES
dc.format.number2es_ES
dc.format.page423-436es_ES
dc.identifier.doi10.21042/AMNS.2016.2.00036es_ES
dc.contributor.funderMinisterio de Economía y Competitividad (España)
dc.contributor.funderComunidad Autónoma Castilla La Mancha
dc.contributor.funderJames S. Mc. Don-nell Foundation (USA)
dc.description.peerreviewedes_ES
dc.identifier.e-issn2444-8656
dc.relation.publisherversionhttps://doi.org/10.21042/AMNS.2016.2.00036es_ES
dc.identifier.journalApplied Mathematics and Nonlinear Scienceses_ES
dc.repisalud.centroISCIII::Unidad Funcional de Investigación de Enfermedades Crónicas (UFIEC)es_ES
dc.repisalud.institucionISCIIIes_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/ES/MTM2012-31073es_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/ES/MTM2015-71200-Res_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/ES/PEII-2014-031-Pes_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/ES/RD12/0036/0027es_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/ES/SAF2015-65175-Res_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES


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Attribution-NonCommercial-NoDerivatives 4.0 Internacional
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