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

Soria, D, Garibaldi, JM, Ambrogi, F, Green, AR, Powe, D, Rakha, E, Macmillan, RD, Blamey, RW, Ball, G ORCID: https://orcid.org/0000-0001-5828-7129, Lisboa, PJG, Etchells, TA, Borracch, P, Biganzoli, E and Ellis, IO, 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), pp. 318-330. ISSN 1862-8346

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Item Type:	Journal article
Publication Title:	Computers in Biology and Medicine
Creators:	Soria, D., Garibaldi, J.M., Ambrogi, F., Green, A.R., Powe, D., Rakha, E., Macmillan, R.D., Blamey, R.W., Ball, G., Lisboa, P.J.G., Etchells, T.A., Borracch, P., Biganzoli, E. and Ellis, I.O.
Publisher:	Elsevier
Date:	2010
Volume:	40
Number:	3
ISSN:	1862-8346
Identifiers:	Number Type 10.1002/prca.200900218 DOI
Divisions:	Schools > School of Science and Technology
Record created by:	EPrints Services
Date Added:	09 Oct 2015 09:52
Last Modified:	09 Jun 2017 13:13
URI:	https://irep.ntu.ac.uk/id/eprint/4091

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