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dc.contributorUniversitat Ramon Llull. La Salle
dc.contributorCarnegie Mellon University
dc.contributorHospital Clinic i Provincial de Barcelona
dc.contributor.authorNicolàs Sans, Rubén
dc.contributor.authorVernet Bellet, David
dc.contributor.authorGolobardes, Elisabet
dc.contributor.authorFornells Herrera, Albert
dc.contributor.authorTorre Frade, Fernando de la
dc.contributor.authorPuig, Susana
dc.date.accessioned2021-06-30T05:58:17Z
dc.date.accessioned2023-07-13T09:53:33Z
dc.date.available2021-06-30T05:58:17Z
dc.date.available2023-07-13T09:53:33Z
dc.date.issued2011-12
dc.identifier.urihttp://hdl.handle.net/20.500.14342/2998
dc.description.abstractCurrent social habits in solar exposure have increased the appearance of melanoma cancer in the last few years. The highest mortality rates in dermatological cancers are caused for this illness. In spite of it, recent studies demonstrate that early diagnosis increases life expectancy. This work introduces a way to classify dermatological cancer with highest rates of accuracy, specificity and sensitivity. The approach is the result of the improvement of previous works that combine information of two of the most important non-invasive image techniques: Reflectance Confocal Microscopy and Dermatoscopy. Current work achieve better results than the previous systems by the use of Distance Metric Learning to the different Case Memories.eng
dc.format.extent9 p.cat
dc.language.isoengcat
dc.publisherThe 14th Workshop on Case-based reasoning at the 29th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, Cambridge, 13-15 of December 2011cat
dc.relation.ispartofProceedings of the 14th Workshop on Case-based reasoning at the 29th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligencecat
dc.rights© L'autor/a. Tots el drets reservats
dc.sourceRECERCAT (Dipòsit de la Recerca de Catalunya)
dc.subject.otherMelanomacat
dc.subject.otherDermatologiacat
dc.subject.otherMedicina -- Innovacionscat
dc.titleApplying Distance Metric Learning in a Collaborative Melanoma Diagnosis System with Case-Based Reasoningcat
dc.typeinfo:eu-repo/semantics/conferenceObjectcat
dc.rights.accessLevelinfo:eu-repo/semantics/openAccess
dc.embargo.termscapcat
dc.subject.udc616.5
dc.subject.udc62


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