Probabilistic classification of age by third molar development: the use of soft evidence.

This study introduces a method to classify individuals according to an age threshold, given sex and third molars' dental maturity measured on the Demirjian scale by expressing uncertainty on dental evidence (soft evidence). We introduced a procedure to learn the parameters of the Naïve Bayes model, and we discussed two classification rules. The model was estimated and tested on 559 Italians aged 16-22. Two experts provided the dental evaluations, and the model was estimated for each of them. We evaluated the coherence of the evidence provided by the experts. Some indexes have been proposed to evaluate the effectiveness of the models, emphasizing how the experts' ability and the technology affect the results. We introduced two benchmarks, one based on the sample distribution per sex and age: in this case, probability of correct classification increases 22% and the proportion of false adults impressively decreases 80.2%; the other benchmark, obtained by simulating hard evidence, shows how the use of soft evidence increases the proportion of correct classification 3.1% and decreases the crucial proportion of false adults about 20%. Similarly, the proportion of false minors decreases about 5.3%.