Artificial Intelligence–Based Multi-Stage System for Automated Angle’s Classification of Malocclusion from Intraoral Images in Orthodontics

Key Points

• Automated classification of malocclusion could enhance orthodontic diagnostics, improving treatment planning.
• The system achieves high accuracy in identifying malocclusions from intraoral images, with a 95% classification rate.
• Using an artificial intelligence framework, this approach incorporates multi-stage processing to improve accuracy.
• Implementation of this automated system may significantly reduce the time taken for orthodontic assessments.