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

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.

doi:10.1016/j.compbiomed.2010.01.003

All Outputs (1)

A methodology to identify consensus classes from clustering algorithms applied to immunohistochemical data from breast cancer patients (2010)
Journal Article
Soria, D., Garibaldi, J. M., Ambrogi, F., Green, A. R., Powe, D., Rakha, E., …Ellis, I. O. (2010). A methodology to identify consensus classes from clustering algorithms applied to immunohistochemical data from breast cancer patients. Computers in Biology and Medicine, 40(3), https://doi.org/10.1016/j.compbiomed.2010.01.003

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’... Read More about A methodology to identify consensus classes from clustering algorithms applied to immunohistochemical data from breast cancer patients.