Prediction of Age Based on Development of Mandibular Third Molars in Sri Lankan Population

Abstract

Age estimation is fundamental to forensic expertise and clinical medicine. The third molar offers one of the unique benefits that proceed over a more extended period. Demirjian’s method is used to classify the third molar development based on eight stages. The stages were allocated a biologically weighted score for each gender. The main objective of this study is to predict the age of subadults based on the third molar development stages. Each third molar development stage was analyzed according to their side and gender. In this study, 1643 left lower third molars and 1665 right lower third molars are considered for analysis, and the third molars’ development stages were recorded in the age group from 10 to 28. Generalized Linear Mixed Model (GLMM), classification and regression tree algorithm (CART), Ridge regression, and Elastic net regression were used to predict the age. Results were validated using the cross-validation technique. Root mean squared error (RMSE), mean absolute error (MAE), and R-squared values were used to select the best model. There were significant differences between the male and female third molars, and there were no significant differences between the left and right lower third molars. Weighted Demirjian’s stages and gender were the significant variables of the fitted models for predicting age. The best model for the prediction of age was the classification and regression tree algorithm (CART), which gave the highest accuracy (70.6%) with the minimum root mean squared error (RMSE = 2.27). Therefore, the classification and regression tree algorithm (CART) can be used to predict the age using the development stages of third molars.