RBF kernel method and its applications to clinical data

نویسندگان

  • Emma Perracchione
  • Ilaria Stura
چکیده

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 measurements 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.

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تاریخ انتشار 2016