Artificial Intelligence for Predicting Difficult Airways: A Review.

ABSTRACT: Background: Accurately predicting difficult airways is essential to ensuring patient safety in anesthesiology and emergency medicine. However, traditional assessment tools often lack sufficient sensitivity and specificity, particularly in high-pressure or resource-limited settings. Artificial intelligence (AI) and machine learning (ML) have emerged as promising tools for enhancing airway assessment. Objective: This review evaluates the performance of AI- and ML-based models for predicting difficult airways and compares them with traditional clinical methods. The review also analyzes the models' methodological robustness, clinical applicability, and ethical considerations. Methods: A comprehensive literature search was conducted across PubMed, Web of Science, and Scopus

SUBMITTER: Alatau M 

PROVIDER: S-EPMC12693205 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature