Cancer profiles by affinity propagation

Federico Ambrogi, Elena Raimondi, Daniele Soria, Patrizia Boracchi, Elia Biganzoli

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish
Title of host publicationProceedings - 7th International Conference on Machine Learning and Applications, ICMLA 2008
Pages650-655
Number of pages6
DOIs
Publication statusPublished - 2008
Event7th International Conference on Machine Learning and Applications, ICMLA 2008 - San Diego, CA, United States
Duration: Dec 11 2008Dec 13 2008

Other

Other7th International Conference on Machine Learning and Applications, ICMLA 2008
CountryUnited States
CitySan Diego, CA
Period12/11/0812/13/08

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Software

Cite this

Ambrogi, F., Raimondi, E., Soria, D., Boracchi, P., & Biganzoli, E. (2008). Cancer profiles by affinity propagation. In Proceedings - 7th International Conference on Machine Learning and Applications, ICMLA 2008 (pp. 650-655). [4725044] https://doi.org/10.1109/ICMLA.2008.110