RBF kernel method and its applications to clinical data
| Title | RBF kernel method and its applications to clinical data |
| Publication Type | Journal Article |
| Year of Publication | 2016 |
| Authors | Perracchione, E, Stura, I |
| Journal | Dolomites Research Notes on Approximation |
| Volume | 9 |
| Issue | Special_Issue |
| Pagination | 13-18 |
| Date Published | 09/2016 |
| Publisher | Padova University Press |
| Place Published | Padova, IT |
| ISSN Number | 20356803 |
| 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. |
| URL | http://drna.padovauniversitypress.it/2016/specialissue/3 |
| DOI | 10.14658/pupj-drna-2016-Special_Issue-3 |
