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RBF kernel method and its applications to clinical data

TitleRBF kernel method and its applications to clinical data
Publication TypeJournal Article
Year of Publication2016
AuthorsPerracchione, E, Stura, I
JournalDolomites Research Notes on Approximation
Volume9
IssueSpecial_Issue
Pagination13-18
Date Published09/2016
PublisherPadova University Press
Place PublishedPadova, IT
ISSN Number20356803
Abstract

In this paper, basing our considerations on kernel-based approaches, we propose a new strategy allowing to approximate the prostate cancer dynamics. In particular, starting from several measure- ments of a specific biomarker, we estimate the tumor growth rate. To achieve this aim, we pre-process data via Radial Basis Function (RBF) interpolation. A careful choice of the basis function and of its shape parameter enables us to obtain reliable approximations of the cancer evolution. Numerical evidence supports our findings.

URLhttp://drna.padovauniversitypress.it/2016/specialissue/3
DOI10.14658/pupj-drna-2016-Special_Issue-3