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

doi:http://dx.doi.org/10.1155/2014/351518

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RECERCAT Home > Universitat Ramon Llull > La Salle > Articles publicats a revistes científiques > View document

Use this identifier to quote or link this document: http://hdl.handle.net/2072/374831

dc.contributor	Universitat Ramon Llull. La Salle
dc.contributor	Hospital Clínic i Provincial de Barcelona. Departament de Dermatologia. Unitat de Melanoma
dc.contributor.author	Fornells Herrera, Albert
dc.contributor.author	Golobardes, Elisabet
dc.contributor.author	Corral Torruella, Guiomar
dc.contributor.author	Puig, Susana
dc.contributor.author	Malvehy, Josep
dc.contributor.author	Nicolàs Sans, Rubén
dc.date.accessioned	2020-05-06T08:05:47Z
dc.date.available	2020-05-06T08:05:47Z
dc.date.created	2013-08
dc.date.issued	2014-01
dc.identifier.uri	http://hdl.handle.net/2072/374831
dc.format.extent	11 p.
dc.language.iso	eng
dc.publisher	Hindawi Publishing Corporation
dc.relation.ispartof	The Scientific World Journal. 2014
dc.rights	L'accés als continguts d'aquest document queda condicionat a l'acceptació de les condicions d'ús establertes per la següent llicència Creative Commons:http://creativecommons.org/licenses/by/4.0/
dc.rights	© L'autor/a
dc.source	RECERCAT (Dipòsit de la Recerca de Catalunya)
dc.subject.other	Melanoma
dc.subject.other	Dermatologia
dc.title	DERMA: A Melanoma Diagnosis Platform Based on Collaborative Multilabel Analog Reasoning
dc.type	info:eu-repo/semantics/article
dc.type	info:eu-repo/semantics/publishedVersion
dc.embargo.terms	cap
dc.relation.projectID	info:eu-repo/grantAgreement/SUR del DEC/SGR/2009 SGR 183
dc.relation.projectID	info:eu-repo/grantAgreement/SUR del DEC /FI/2010 FI_B20084
dc.identifier.doi	http://dx.doi.org/10.1155/2014/351518
dc.rights.accessLevel	info:eu-repo/semantics/openAccess
dc.description.abstract	The number of melanoma cancer-related death has increased over the last few years due to the new solar habits. Early diagnosishas become the best prevention method. This work presents a melanoma diagnosis architecture based on the collaboration ofseveral multilabel case-based reasoning subsystems called DERMA. The system has to face up several challenges that include datacharacterization, pattern matching, reliable diagnosis, and self-explanation capabilities. Experiments using subsystems specializedin confocal and dermoscopy images have provided promising results for helping experts to assess melanoma diagnosis.

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