Identification of relevant knowledge for characterizing the melanoma domain

Ruben Nicolas, Elisabet Golobardes, Albert Fornells, Susana Puig, Cristina Carrera, Josep Malvehy

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

2 Cites (Scopus)


Melanoma is one of the most important cancers to study in our current social context. This kind of cancer has increased its frequency in the last few years and its mortality is around twenty percent if it is not early treated. In order to improve the early diagnosis, the problem characterization using Machine Learning (ML) is crucial to identify melanoma patterns. Therefore we need to organize the data so that we can apply ML on it. This paper presents a detailed characterization based on the most relevant knowledge in melanomas problem and how to relate them to apply Data Mining techniques to aid medical diagnosis in melanoma and improve the research in this field.

Idioma originalAnglès
Títol de la publicació2nd International Workshop on Practical Applications of Computational Biology and Bioinformatics (IWPACBB 2008)
EditorsJuan Corchado, Juan De Paz, Miguel Rocha, Florentino Fernandez Riverola
Nombre de pàgines5
Estat de la publicacióPublicada - 2009

Sèrie de publicacions

NomAdvances in Soft Computing
ISSN (imprès)1615-3871
ISSN (electrònic)1860-0794


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