Technical Report Details
| Date |
15-5-2008 |
| Number |
DISI-TR-08-13 |
| Title |
A Statistical Learning approach to Liver Iron Overload Estimation |
| Authors |
L. Baldassarre, B. Gianesin, A. Barla, M. Marinelli |
| Bibtex Entry |
@techrep{DISI-TR-08-13,
author = {L. Baldassarre, B. Gianesin, A. Barla, M. Marinelli},
title = {A |
| E-mail |
baldassarre@disi.unige.it |
| Link |
http://slipguru.disi.unige.it/Downloads/publications/DISI-TR-08-13.pdf |
| Abstract |
In this work we present and discuss in detail a novel vector-valued regression technique: our approach allows for an all-at-once estimation of the vector components, as opposed to solve a number of independent scalar-valued regression tasks. Despite its general purpose nature, the method has been designed to solve a delicate medical issue: a reliable and non-invasive assessment of body-iron overload.
The Magnetic Iron Detector (MID) measures the magnetic track of a person, which depends on the anthropometric characteristics and the body-iron burden. We aim to provide an estimate of this signal in absence of iron overload. We show how this question can be formulated as the estimation of a vector-valued function which encompasses the prior knowledge on the shape of the magnetic track. This is accomplished by designing an appropriate vector-valued feature map. We successfully applied the method on a dataset of 84 volunteers. |
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