Title :
Cancer Profiles by Affinity Propagation
Author :
Ambrogi, Federico ; Raimondi, Elena ; Soria, Daniele ; Boracchi, Patrizia ; Biganzoli, Elia
Author_Institution :
Ist. di Statistica Medica e Biometria "GA Maccacaro ", Univ. degli Studi di Milano, Milan
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.
Keywords :
cancer; medical computing; pattern clustering; statistical analysis; affinity propagation algorithm; breast cancer subtyping; cancer profiles; clustering techniques; genomic analysis; Bioinformatics; Breast cancer; Clustering algorithms; Computer science; Erbium; Genomics; Inspection; Machine learning; Malignant tumors; Pathology;
Conference_Titel :
Machine Learning and Applications, 2008. ICMLA '08. Seventh International Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
978-0-7695-3495-4
DOI :
10.1109/ICMLA.2008.110