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dc.contributorUniversitat Ramon Llull. La Salle
dc.contributorUniversitat de Girona
dc.contributor.authorFornells Herrera, Albert
dc.contributor.authorGolobardes, Elisabet
dc.contributor.authorBernado Mansilla, Ester
dc.contributor.authorMartí Bonmatí, Joan
dc.date.accessioned2021-06-02T19:35:20Z
dc.date.accessioned2023-07-13T09:52:45Z
dc.date.available2021-06-02T19:35:20Z
dc.date.available2023-07-13T09:52:45Z
dc.date.created2006-05
dc.date.issued2006-05
dc.identifier.urihttp://hdl.handle.net/20.500.14342/2939
dc.description.abstractThe incidence of breast cancer varies greatly among countries, but statistics show that every year 720,000 new cases will be diagnosed world-wide. However, a low percentage of women who suffer it can be detected using mammography methods. Therefore, it is necessary to develop new strategies to detect its formation in early stages. Many machine learning techniques have been applied in order to help doctors in the diagnosis decision process, but its definition and application are complex, getting results which are not often the desired. In this article we present an automatic way to build decision support systems by means of the combination of several machine learning techniques using a Meta-learning approach based on Grammar Evolution (MGE). We will study its application over different mammographic datasets to assess the improvement of the results.eng
dc.format.extent8 p.cat
dc.language.isoengcat
dc.publisherEighth International Conference on Enterprise Information Systems, May 23-27, 2006, in Paphos, Cypruscat
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights© SciTePress
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.sourceRECERCAT (Dipòsit de la Recerca de Catalunya)
dc.subject.otherIntel·ligència artificial -- Aplicacions a la medicinacat
dc.subject.otherMedicina -- Informàticacat
dc.titleDecision Support System for the Breast Cancer Diagnosis by a Meta-learning Approach based on Grammar Evolutioncat
dc.typeinfo:eu-repo/semantics/articlecat
dc.typeinfo:eu-repo/semantics/publishedVersioncat
dc.rights.accessLevelinfo:eu-repo/semantics/openAccess
dc.embargo.termscapcat
dc.subject.udc004
dc.subject.udc61
dc.subject.udc62
dc.identifier.doihttps://doi.org/10.5220/0002492202220229cat


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Attribution-NonCommercial-NoDerivatives 4.0 International
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