User influence on fully automated cephalometric tracing using an artificial intelligence-driven online platform: pilot study

ABSTRACT Objective: The aim of this study was to evaluate the diagnostic reliability of automated tracings compared with the modifications made by the user. Methods: This observational analytical cross-sectional study used 44 lateral cephalograms, analyzed in the WebCeph™ software by a trained observer. The angles evaluated were those specified by the Brazilian Board of Orthodontics. The first evaluation was performed by the software’s artificial intelligence, and the results were recorded. In the second evaluation, the user checked the position of the landmarks and modified them if necessary. The results were subjected to statistical analysis. Results: There was a statistically significant correlation between the user and AI (p<0.05). The user modified 88.63% of the sample. The most modified landmarks were the nasion, B, U1 border, and L1 border. Conclusion: There was technical agreement between AI and user, with the values obtained being equivalent. The AI diagnosis is reliable, but user experience remains fundamental for the final diagnosis.