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DERMA: A Melanoma Diagnosis Platform Based on Collaborative Multilabel Analog Reasoning

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 multilabel case-based reasoning subsystems...

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Detalles Bibliográficos
Autores principales: Nicolas, Ruben, Fornells, Albert, Golobardes, Elisabet, Corral, Guiomar, Puig, Susana, Malvehy, Josep
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3918694/
https://www.ncbi.nlm.nih.gov/pubmed/24578629
http://dx.doi.org/10.1155/2014/351518
Descripción
Sumario: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 multilabel case-based reasoning subsystems called DERMA. The system has to face up several challenges that include data characterization, pattern matching, reliable diagnosis, and self-explanation capabilities. Experiments using subsystems specialized in confocal and dermoscopy images have provided promising results for helping experts to assess melanoma diagnosis.