A methodology to identify consensus classes from clustering algorithms applied to immunohistochemical data from breast cancer patients

A methodology to identify consensus classes from clustering algorithms applied to immunohistochemical data from breast cancer patients

Single clustering methods have often been used to elucidate clusters in high dimensional medical data, even though reliance on a single algorithm is known to be problematic. In this paper, we present a methodology to determine a set of ‘core classes’ by using a range of techniques to reach consensus...

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Bibliographic Details
Main Authors: Soria, Daniele, Garibaldi, Jonathan M., Ambrogi, Federico, Green, Andrew R., Powe, Des, Rakha, Emad, Douglas Macmillan, R., Blamey, Roger W., Ball, Graham, Lisboa, Paulo J.G., Etchells, Terence A., Boracchi, Patrizia, Biganzoli, Elia M., Ellis, Ian O.
Format: Article
Published: Elsevier 2010
Online Access:https://eprints.nottingham.ac.uk/28133/

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