Driven by the growing demand of personalization of medical procedures, data-based, computer-aided cancer research in human patients is advancing at an accelerating pace, providing a broadening landscape of opportunity for Machine Learning methods. This landscape can be observed from the wide-reaching view of population studies down to the genotype detail. In this brief paper, we provide a sweeping glimpse, by no means exhaustive, of the state-of-the-art in this field at the different scales of data measurement and analysis.
Machine learning in cancer research : implications for personalised medicine / E.A. Vellido, E. Biganzoli, P.J.G. Lisboa - In: ESANN 2008 proceedings : Advances in computational intelligence and learning : Bruges (Belgium), 23-25 April 2008Louvain-la-Neuve : Université catholique de Louvain, 2008. - ISBN 2-930307-08-0. - pp. 55-64 (( Intervento presentato al 16. convegno European Symposium on Artificial Neural Network (ESANN) tenutosi a Bruges nel 2008.
Machine learning in cancer research : implications for personalised medicine
E. BiganzoliSecondo
;
2008
Abstract
Driven by the growing demand of personalization of medical procedures, data-based, computer-aided cancer research in human patients is advancing at an accelerating pace, providing a broadening landscape of opportunity for Machine Learning methods. This landscape can be observed from the wide-reaching view of population studies down to the genotype detail. In this brief paper, we provide a sweeping glimpse, by no means exhaustive, of the state-of-the-art in this field at the different scales of data measurement and analysis.
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