Towards Artificial Intelligence-enabled Medical Pre-operative Airway Assessment
Author:
Affiliation:
1. National University of Singapore,College of Design and Engineering,Singapore
2. University Hospital,Department of Anaesthesia National,Singapore
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9982624/9982728/09982781.pdf?arnumber=9982781
Reference27 articles.
1. Validity of thyromental height test as a predictor of difficult laryngoscopy: A prospective evaluation comparing modified Mallampati score, interincisor gap, thyromental distance, neck circumference, and neck extension;rao;Indian J Anaesth,2018
2. A comparison of Mallampati classification, thyromental distance and a combination of both to predict difficult intubation;mallhi;Anaesth Pain & Intensive Care,2018
3. Faceness-Net: Face Detection through Deep Facial Part Responses
4. Annotated Facial Landmarks in the Wild: A large-scale, real-world database for facial landmark localization
5. Cross-pose lfw: A database for studying cross-pose face recognition in unconstrained environments;zheng;Beijing University of Posts and Telecommunications,2018
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