Artificial intelligence-based [A.I.] assessment of Facial symmetry aesthetics of Saudi Arabian population.

Abstract

Objective: The purpose of this study is to investigate the facial symmetry aesthetics (FSA) in the Saudi Arabian population using AI.

Materials and methods: 210 people from a range of demographic backgrounds participated in an observational cross-sectional study that was done at a hospital. Standardized posed photos of the face and smile were taken using a Canon camera utilizing a stratified random sample approach. A Webceph software (Korea) with artificial intelligence was used to evaluate macro, micro, and tiny aesthetic factors. The data were analyzed using paired t-tests, posthoc Bonferroni testing, ANOVA, and descriptive statistics. The computation of intra-class correlation coefficients (ICCs) was utilized to assess the dependability of AI evaluations.

Results: All variables had ICCs more than 0.97, indicating exceptional dependability for the AI-based evaluations. Between the Class I and Class III malocclusion groups, there were significant variations in right mandibular body length (p < 0.001), with Class III patients exhibiting greater values. While no significant changes were identified for other characteristics, paired t-tests showed a significant divergence in mandibular body length between the right and left sides (p = 0.001). In Class III malocclusion, there was a significant preference for right deviation in the direction of mandibular deviation (p = 0.005). These results imply that AI is capable of accurately identifying some anatomical characteristics associated with face aesthetics, especially when it comes to differentiating between Class III malocclusions.

Conclusion: In conclusion, the Saudi Arabian population's facial symmetry assessments via AI have demonstrated a high degree of reliability and consistency. Notably, the length of the mandible on the right side has emerged as a crucial feature in discriminating between malocclusion classes. The study emphasises how AI might improve the accuracy of assessments of face aesthetics and our knowledge of facial features connected to malocclusion.