Although there is no related research on the evaluation of difficult airways by ultrasound features based on artificial intelligence, the investigators guess that the evaluation of ultrasound features based on artificial intelligence can make further breakthroughs in difficult airway early warning systems. Therefore, this project intends to use AI technology to extract and analyze the ultrasound features of the subjects, evaluate the correlation between the ultrasound features of the subjects and the occurrence of difficult airways, and construct possible diagnostic models to evaluate AI ultrasound feature recognition in the prediction of difficult airways. The effect and application value of this method are expected to be more intelligent and accurate for early warning of difficult airways in clinical anesthesia.

Inclusion Criteria:

• ASA classification is 1-3
• Patients who intend to undergo tracheal intubation under general anesthesia
• Age ≥ 18 years old

Exclusion Criteria:

• Patients with speech communication and cooperation barriers;
• Patients with open head and neck trauma
• Patients with cervical spine fractures or cervical spine diseases;
• Emergency surgery;
• Patients who are allergic to related drugs.

adults who intend to undergo tracheal intubation under general anesthesia