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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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