Establishment of Airway Database for Surgical Patients

Artificial Intelligence, Difficult Airway

Difficult airway is a major reason of anesthesia related injuries with latent life threatening complications. Foresee difficult airway in the preoperative period is vital for the patient's safety. The aim of this study is to develop a computer algorithm that can detect whether the patient is a difficult airway based on photographs form six aspects. This method will be decreased potential complication related to difficult airway and increased patient safety.

Introduction: The primary purpose of the study is to develop a computer algorithm that can detect whether the patient is a difficult airway based on photographs from six different aspects. Methods: This study is divided into two parts. In the first part, we collected the patients' airway assessment score who underwent general anesthesia with endotracheal intubation assessed by an experienced attending anesthesiologists before and after intubation. Evaluation of airway score after tracheal intubation as the gold standard for airway assessment. Digital photographs of the face of each patient in frontal neutral view and in profile neutrals were obtained. Details of the photographs, each corresponding to a facial motion: (1) Frontal, neutral. (2) Frontal, mouth open. (3)Frontal, extreme mouth open and tongue out. (4)Frontal, extreme upper lip bite (5)Profile, neutral. (6) Profile, neutral, maximum head back. The patient's photographs and the airway evaluation score after intubation were input to the computer to train the computer. In the second part, the trained computer was used to evaluate the airway score of the new patient compared with that of the patient after intubation, and calculated the sensitivity.

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