A Deep Metric Learning and Multimodal Gated Fusion Framework for AI-Driven Risk Assessment of Lingual Plate Perforation and Mandibular Canal Injury in Posterior Mandible Implants.

Key Points

• The study aims to improve risk assessment for lingual plate perforation and mandibular canal injury during implant procedures using AI techniques.
• Integrated imaging and metadata using deep metric learning (DML).
• Applied a multimodal gated fusion (GFM) framework.
• Focused on reducing interoperator variability in treatment planning.
• Enhanced accuracy in risk classification for implant treatments.
• Reduced discrepancies in decision-making among different operators.