This prospective observational study aims to develop an artificial intelligence model that can automatically determine the Cormack-Lehane classification from video laryngoscopy images in patients undergoing elective surgery. It also aims to predict the risk of difficult intubation based on this classification. The resulting data will evaluate the applicability of AI-supported decision support systems in clinical airway management.
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AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
Accuracy of Machine Learning Model in Predicting Difficult Intubation Based on Video Laryngoscopy Images
Timeframe: Immediately after data collection and model training