Exploration and Application of Intelligent Difficult Airway Assessment Scheme

The study aims to explore the effectiveness of an intelligent difficult airway assessment protocol and its potential in clinical applications. The management of difficult airways is a critical task in anesthesiology, and poor management can lead to severe complications or even death. The American Society of Anesthesiologists defines a difficult airway as one that presents difficulties in mask ventilation or endotracheal intubation. Previous studies have shown that the incidence of difficult airways is not low in patients undergoing general anesthesia, emphasizing the need for optimization of airway management strategies. Preoperative airway assessment is an essential step in preventing complications associated with difficult airways. Currently, the modified Mallampati classification and the Cormack-Lehane grading are two commonly used assessment tools. However, these methods rely on the subjective judgment of clinicians and may have limitations in accuracy and consistency. With the development of artificial intelligence and telemedicine technologies, new assessment methods have become possible, offering more precise measurements and analysis of airway anatomy. This study proposes an intelligent airway assessment system that combines phonation modulation and tongue position adjustment, aiming to improve the accuracy and reliability of assessments. The system uses deep learning algorithms to analyze oral images of subjects to predict airway difficulty. The study will also explore the correlation of this system with traditional assessment methods and establish a predictive model for difficult airways. As a country with a large population, China has a significant demand for medical and health resources, especially in the fields of surgery and anesthesia. The diversity of China's population may affect airway structure, thereby influencing airway management strategies. Therefore, conducting such research in China has important clinical significance and social value.