Prediction of mandibular morphology through artificial neural networks

Abstract

Prediction 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.