Experiences using clustering and generalizations for knowledge discovery in melanomas domain

A. Fornells, E. Armengol, E. Golobardes, S. Puig, J. Malvehy

Producció científica: Capítol de llibreContribució a una conferènciaAvaluat per experts

5 Cites (Scopus)


One of the main goals in prevention of cutaneous melanoma is early diagnosis and surgical excision. Dermatologists work in order to define the different skin lesion types based on dermatoscopic features to improve early detection. We propose a method called SOMEX with the aim of helping experts to improve the characterization of dermatoscopic melanoma types. SOMEX combines clustering and generalization to perform knowledge discovery. First, SOMEX uses Self-Organizing Maps to identify groups of similar melanoma. Second, SOMEX builds general descriptions of clusters applying the anti-unification concept. These descriptions can be interpreted as explanations of groups of melanomas. Experiments prove that explanations are very useful for experts to reconsider the characterization of melanoma classes.

Idioma originalAnglès
Títol de la publicacióAdvances in Data Mining
Subtítol de la publicacióMedical Applications, E-Commerce, Marketing, and Theoretical Aspects - 8th Industrial Conference, ICDM 2008, Proceedings
Nombre de pàgines15
Estat de la publicacióPublicada - 2008
Esdeveniment8th Industrial Conference on Data Mining, ICDM 2008 - Leipzig, Germany
Durada: 16 de jul. 200818 de jul. 2008

Sèrie de publicacions

NomLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volum5077 LNAI
ISSN (imprès)0302-9743
ISSN (electrònic)1611-3349


Conferència8th Industrial Conference on Data Mining, ICDM 2008


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