Melanoma diagnosis based on collaborative multi-label reasoning

Ruben Nicolas, Albert Fornells, Elisabet Golobardes, Guiomar Corral, Susana Puig, Josep Malvehy

Producció científica: Capítol de llibreContribució a congrés/conferènciaAvaluat per experts


The number of melanoma cancer-related death has increased over the last few years due to the new solar habits. Early diagnosis has become the best prevention method. This work presents a melanoma diagnosis architecture based on the collaboration of several multi-label case-based reasoning subsystems called DERMA. The system has to face several challenges that include data characterization, pattern matching, reliable diagnosis and self-explanation capabilities. Experiments using two subsystems specialized in confocal and dermoscopy data from images respectively have provided promising results to help experts assess melanoma patterns.

Idioma originalAnglès
Títol de la publicacióArtificial Intelligence Research and Development. Proceedings of the 16th International Conference of the Catalan Association for Artificial Intelligence
EditorsKarina Gibert, Vicent Botti, Ramon Reig-Bolano
Nombre de pàgines10
Estat de la publicacióPublicada - 2013

Sèrie de publicacions

NomFrontiers in Artificial Intelligence and Applications
ISSN (imprès)0922-6389


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