ImpactU Versión 3.11.2 Última actualización: Interfaz de Usuario: 16/10/2025 Base de Datos: 29/08/2025 Hecho en Colombia
Uso de redes neuronales artificiales en predicción de morfología mandibular a través de variables craneomaxilares en una vista posteroanterior / Use of Artificial Neural Networks for Mandibular Morphology Prediction through Craniomaxillar Variables...
<p><em><strong><span>Background:</span></strong></em><span class="apple-converted-space"><span> </span></span><span>Predicting mandibular morphology is important in facial reconstruction for forensic purposes as in orthodontics and maxillofacial surgery. This process has been performed through parametric and linear methods based on Caucasian populations. Also, these analyzes are performed on lateral cephalograms, but a prediction from a posteroanterior view is not taken into account.<span class="apple-converted-space"> </span><em><strong>Purpose:</strong></em><span class="apple-converted-space"> </span>To predict through artificial neural networks the mandibular morphology using craniomaxillary measures in posteroanterior radiographs.<span class="apple-converted-space"> </span><em><strong>Methods:</strong></em><span class="apple-converted-space"> </span>229 standardized posteroanterior radiographs from Colombian young adults of both sexes were collected. Coordinates of craniofacial skeletal landmarks were used to create mandibular and craniomaxillary measures. 17 predictor craniomaxillary input variables were selected, measuring widths, heights, and angles. Similarly, 13 mandibular measures were selected to be predicted, considering both the right and left sides. Artificial neural networks were used for the prediction process and it was evaluated by a correlation coefficient using a ridge regression between real value and the predicted value.<span class="apple-converted-space"> </span><em><strong>Results:</strong></em><span class="apple-converted-space"> </span>The results found in the model were significant especially for 5 variables of morphological importance in the forensic field: right mandibular ramus (Cdd-God), bigonial width (Goi-God), bicondylar width (Cdi-Cdd), and distance between the condyles to the menton (Cdd-Me and Cdi-Me).<span class="apple-converted-space"> </span><em><strong>Conclusions:</strong></em><span class="apple-converted-space"> </span>An important prediction capacity in 5 measures of forensic importance in patients with skeletal Class I, Class II and Class III was found in both sexes.</span></p>