Impact of artificial intelligence (AI) on predicting marginal fit and aesthetic outcomes for custom implant abutments.

Abstract

The integration of artificial intelligence into implant prosthodontics enhances the precision of pre-fabrication predictions for clinical success. In this study, a custom convolutional neural network (CNN) model achieved a prediction accuracy of 93.5% for marginal fit within a 25 µ tolerance and 87.6% concordance with clinical evaluations of custom implant abutment aesthetics. The AI-estimated mean spatial gap (78.6±18.2 µ) closely approximated the actual measurement (82.3 ± 21.5 µ), with strong correlations observed between predicted and actual outcomes for both fit (r = 0.89) and aesthetic appeal (r = 0.82-0.85). Thus, we show the potential of AI as a preventive quality assessment tool in implant prosthodontics, capable of minimizing adjustments and remakes while improving overall clinical success rates.