Gender determination is a fundamental issue in forensic anthropology. Many techniques based on bone and dental remains have been proposed. It is not always possible to implement the techniques using bones, but teeth are often perfectly preserved. It has been demonstrated that the canine has the greatest sexual dimorphism, and the aim of this work was to provide an easy and accurate dental technique for determining the gender in the absence of other skeletal elements. The sample was composed of 210 CT scans with four healthy canines. The 840 canines were modeled using MIMICS â 10.01 software. The total volume of each tooth was determined. Seven mathematical models were determined by binary logistic regressions and ranked in order of relative performance. The seven proposed predictive models thus performed (0.910 ≤ AUC ≤ 0.938), with overall rates of correct predictions between 82.38 and 85.24%. The 4-canine model is the most powerful for predicting the gender.
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