Artificial Intelligence-Assisted Sex Estimation from Canine Measurements on Panoramic Radiographs: Comparison with Manual Analysis in a Romanian Sample

Background: Odontometrics is useful for sex estimation when other skeletal elements are missing or when DNA analysis is not feasible due to the greater durability of teeth under various taphonomic factors. The aim of this study was to evaluate canine odontometrics in a Romanian sample using manual versus AI-based measurements and to compare these two methods. Methods: Out of 200 orthopantomograms, 134 (64 females, 70 males) met the inclusion and exclusion criteria and were analyzed. Manual and AI-based measurements were used to assess total canine length and canine distance. Subsequently, statistical analyses were performed to estimate the accuracy of sex discrimination between the two groups. Results: Inter-observer agreement was excellent (ICC = 0.923–0.992). Mandibular canines, particularly tooth 33, provided the strongest sex-discriminatory performance in both manual and AI-derived measurements, with cross-validated accuracy values of 69.4% (manual) and 64.9% (AI); intercanine distances showed lower discriminatory value. The multivariate manual and AI models achieved comparable performance (AUC = 0.765 vs. 0.732), with no statistically significant difference between the two approaches (p = 0.375). Conclusions: AI-based and manual measurements showed comparable sex-estimation performance in this sample. Given its accuracy, this approach should be applied as part of an integrated forensic assessment rather than as a stand-alone method.