On some descriptive and predictive methods for the dynamics of cancer growth
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Title
On some descriptive and predictive methods for the dynamics of cancer growthDate
2015-01Publisher
Alma Mater Studiorum - Università di BolognaBibliographic citation
VLAD, Iulian T.; MATEU, Jorge; ROMANO, Elvira. On some descriptive and predictive methods for the dynamics of cancer growth. Statistica, 2015, vol. 75, no 3, p. 247.Type
info:eu-repo/semantics/articlePublisher version
https://search.proquest.com/docview/1789077551/3DB79D3FE32C4E3CPQ/1?accountid=15297Version
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Abstract
Cancer is a widely spread disease that affects a large proportion of the human population, and many research teams are developing algorithms to help medics to understand this disease. In particular, tumor growth has ... [+]
Cancer is a widely spread disease that affects a large proportion of the human population, and many research teams are developing algorithms to help medics to understand this disease. In particular, tumor growth has been studied from different viewpoints and several mathematical models have been proposed. In this paper, we review a set of comprehensive and modern tools that are useful for prediction of cancer growth in space and time. We comment on three alternative approaches. We first consider spatio-temporal stochastic processes within a Bayesian framework to model spatial heterogeneity, temporal dependence and spatio-temporal interactions amongst the pixels, providing a general modeling framework for such dynamics. We then consider predictions based on geometric properties of plane curves and vectors, and propose two methods of geometric prediction. Finally we focus on functional data analysis to statistically compare tumor contour evolutions. We also analyze real data on brain tumor. [-]
Investigation project
Ministry of Economy and Competitivity (Grants P1-1B2012-52, and MTM2013-43917-P)Rights
info:eu-repo/semantics/openAccess
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- MAT_Articles [766]
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