Cancer profiles by affinity propagation

Ambrogi, Federico, Raimondi, Elena, Soria, Daniele, Boracchi, Patrizia, Biganzoli, Elia (2008) Cancer profiles by affinity propagation. In: Proceedings - 7th International Conference on Machine Learning and Applications, ICMLA 2008. . pp. 650-655. IEEE ISBN 978-1-4244-4061-0. (doi:10.1109/ICMLA.2008.110) (KAR id:98907)

PDF Author's Accepted Manuscript Language: English
Download this file (PDF/104kB)	Preview
Request a format suitable for use with assistive technology e.g. a screenreader
Official URL: https://doi.org/10.1109/ICMLA.2008.110

Abstract

The affinity propagation algorithm is applied to a problem of breast cancer subtyping using traditional biologic markers. The algorithm provides a procedure to determine the number of profiles to be considered. A well know breast cancer case series was used to compare the results of the affinity propagation with the results obtained with standard algorithms and indexes for the optimal choice of the number of clusters. Results from affinity propagation are consistent with the results already obtained having the advantage of providing an indication about the number of clusters. © 2008 IEEE.

Item Type:	Conference or workshop item (Paper)
DOI/Identification number:	10.1109/ICMLA.2008.110
Additional information:	cited By 2
Uncontrolled keywords:	breast cancer
Subjects:	Q Science > QA Mathematics (inc Computing science)
Divisions:	Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User:	Daniel Soria
Date Deposited:	08 Dec 2022 15:42 UTC
Last Modified:	05 Nov 2024 13:04 UTC
Resource URI:	https://kar.kent.ac.uk/id/eprint/98907 (The current URI for this page, for reference purposes)

University of Kent Author Information

Soria, Daniele.

Creator's ORCID:	https://orcid.org/0000-0002-0164-8218
CReDIT Contributor Roles:

Depositors only (login required):

Altmetric

Download Statistics

Total unique views for this document in KAR since July 2020. For more details click on the image.