Experiences using clustering and generalizations for knowledge discovery in melanomas domain

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

*Autor correspondiente de este trabajo

Producción científica: Capítulo del libroContribución a congreso/conferenciarevisión exhaustiva

5 Citas (Scopus)

Resumen

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 originalInglés
Título de la publicación alojadaAdvances in Data Mining
Subtítulo de la publicación alojadaMedical Applications, E-Commerce, Marketing, and Theoretical Aspects - 8th Industrial Conference, ICDM 2008, Proceedings
Páginas57-71
Número de páginas15
DOI
EstadoPublicada - 2008
Evento8th Industrial Conference on Data Mining, ICDM 2008 - Leipzig, Alemania
Duración: 16 jul 200818 jul 2008

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen5077 LNAI
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia8th Industrial Conference on Data Mining, ICDM 2008
País/TerritorioAlemania
CiudadLeipzig
Período16/07/0818/07/08

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