AI in Tongue-Tie and OSA Risk Assessment: From Individual Classifications to Clinical Synthesis

Artificial intelligence is creating new possibilities for clinical assessment of tongue-tie, oral function, airway-related anatomy, and obstructive sleep apnea risk.

These domains are often evaluated through different anatomical and functional classifications, by different professionals, and at different stages of care. Each framework contributes part of the clinical picture, while clinically relevant relationships may remain fragmented when findings are considered separately.

This presentation explores a supportive clinical approach in which artificial intelligence applies multiple established classifications to a single structured oral assessment and synthesizes the findings, bringing them together with the patient’s history, intake information, and reported symptoms. This integrated clinical picture can support more comprehensive interpretation, more informed clinical decision-making, and better treatment planning.