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:
Research Article
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
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author Nicolas, Ruben
Fornells, Albert
Golobardes, Elisabet
Corral, Guiomar
Puig, Susana
Malvehy, Josep
author_facet Nicolas, Ruben
Fornells, Albert
Golobardes, Elisabet
Corral, Guiomar
Puig, Susana
Malvehy, Josep
author_sort Nicolas, Ruben
collection PubMed
description 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.
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spelling pubmed-39186942014-02-26 DERMA: A Melanoma Diagnosis Platform Based on Collaborative Multilabel Analog Reasoning Nicolas, Ruben Fornells, Albert Golobardes, Elisabet Corral, Guiomar Puig, Susana Malvehy, Josep ScientificWorldJournal Research Article 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. Hindawi Publishing Corporation 2014-01-21 /pmc/articles/PMC3918694/ /pubmed/24578629 http://dx.doi.org/10.1155/2014/351518 Text en Copyright © 2014 Ruben Nicolas et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Nicolas, Ruben
Fornells, Albert
Golobardes, Elisabet
Corral, Guiomar
Puig, Susana
Malvehy, Josep
DERMA: A Melanoma Diagnosis Platform Based on Collaborative Multilabel Analog Reasoning
title DERMA: A Melanoma Diagnosis Platform Based on Collaborative Multilabel Analog Reasoning
title_full DERMA: A Melanoma Diagnosis Platform Based on Collaborative Multilabel Analog Reasoning
title_fullStr DERMA: A Melanoma Diagnosis Platform Based on Collaborative Multilabel Analog Reasoning
title_full_unstemmed DERMA: A Melanoma Diagnosis Platform Based on Collaborative Multilabel Analog Reasoning
title_short DERMA: A Melanoma Diagnosis Platform Based on Collaborative Multilabel Analog Reasoning
title_sort derma: a melanoma diagnosis platform based on collaborative multilabel analog reasoning
topic Research Article
url 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
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