Published on in Vol 11, No 1 (2022): Jan-Jun

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/28366, first published .
Machine Learning Approaches for Predicting Difficult Airway and First-Pass Success in the Emergency Department: Multicenter Prospective Observational Study

Machine Learning Approaches for Predicting Difficult Airway and First-Pass Success in the Emergency Department: Multicenter Prospective Observational Study

Machine Learning Approaches for Predicting Difficult Airway and First-Pass Success in the Emergency Department: Multicenter Prospective Observational Study

Journals

  1. García-García F, Lee D, Mendoza-Garcés F, Irigoyen-Miró S, Legarreta-Olabarrieta M, García-Gutiérrez S, Arostegui I. Automated location of orofacial landmarks to characterize airway morphology in anaesthesia via deep convolutional neural networks. Computer Methods and Programs in Biomedicine 2023;232:107428 View
  2. Zhou C, Wang Y, Xue Q, Yang J, Zhu Y. Predicting difficult airway intubation in thyroid surgery using multiple machine learning and deep learning algorithms. Frontiers in Public Health 2022;10 View
  3. Senthilnathan M, Kundra P. Predictive machine learning algorithms in anticipating problems with airway management. Airway 2023;6(1):4 View
  4. Naik N, Mathew P, Kundra P. Scope of artificial intelligence in airway management. Indian Journal of Anaesthesia 2024;68(1):105 View
  5. Dougherty J, Paxton J. Recent Technological Advances in Airway Management. Current Emergency and Hospital Medicine Reports 2024;12(1):32 View

Books/Policy Documents

  1. Wu C, Mathur P. Artificial Intelligence in Clinical Practice. View