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dc.creatorViloria, Amelec
dc.creatorMendinueta, Martha
dc.creatorBorrero, Luz Adriana
dc.creatorPineda, Omar
dc.date.accessioned2021-01-29T21:00:40Z
dc.date.available2021-01-29T21:00:40Z
dc.date.issued2020
dc.identifier.urihttps://hdl.handle.net/11323/7803
dc.description.abstractPrediction models are used for knowing the behavior of highly related complex data. The prediction of morphological structures, and especially the mandible from cranio-maxillary variables, has clinical and investigative odontological usefulness. For example, in cases of trauma, pathologies and in forensic sciences, especially when it is necessary to¬ individualize a missing person, using facial reconstruction. The aim of this paper is to predict mandibular morphology through artificial neuronal networks, using cranio-maxillary measures in posterior-anterior radiographs.spa
dc.format.mimetypeapplication/pdfspa
dc.language.isoengspa
dc.publisherCorporación Universidad de la Costaspa
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.sourceProcedia Computer Sciencespa
dc.subjectArtificial Neural Networksspa
dc.subjectMandibular Bonespa
dc.subjectPredictionspa
dc.titlePrediction of mandibular morphology through artificial neural networksspa
dc.typearticlespa
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dc.type.hasVersioninfo:eu-repo/semantics/publishedVersionspa
dc.source.urlhttps://www.sciencedirect.com/science/article/pii/S1877050920305019#!spa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.identifier.doihttps://doi.org/10.1016/j.procs.2020.03.064


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