THE ROLE OF ARTIFICIAL INTELLIGENCE TRAINED WITH PRE-MEASURED NUMERICAL DATA IN PREDICTION OF DIFFICULT INTUBATION

Launched by KUTAHYA HEALTH SCIENCES UNIVERSITY · Apr 29, 2025

Keywords

ClinConnect Summary

This clinical trial is studying how artificial intelligence (AI) can help predict if a patient will have a difficult time being intubated during surgery. Intubation is a procedure that involves placing a tube in the airway to help patients breathe while they are under general anesthesia. The goal is to improve safety and decision-making for doctors during this critical time. Currently, doctors use physical measurements and assessments to determine the risk of difficult intubation, but these methods can be challenging to perform quickly and accurately. By using AI trained on various data, including images and measurements, the researchers hope to create a more reliable and objective way to predict these challenges.

To participate in the study, individuals must be 18 years or older, scheduled for surgery requiring general anesthesia with intubation, and able to give their consent. Participants will undergo some simple measurements and have photographs taken of their upper bodies. This data will help researchers train the AI model. While the study is not yet recruiting participants, it aims to gather important information that could lead to better predictions of airway difficulties in the future, ultimately enhancing patient safety during surgeries.

Gender

ALL

Eligibility criteria

• Inclusion Criteria:
• • Patients aged 18 years or older
• • Patients scheduled to undergo general anesthesia with endotracheal intubation
• • Patients who provide written informed consent
• • Patients able to undergo preoperative clinical evaluation and imaging without contraindications
• Exclusion Criteria:
• • Patients younger than 18 years of age
• • Pregnant patients
• • Emergency surgery cases
• • Patients with a history of facial surgery altering facial anatomy
• • Patients with a history of head and neck surgery
• • Patients not receiving general anesthesia