Artificial intelligence, machine learning and the pediatric airway.

Clicks: 254
ID: 71307
2019
Artificial intelligence and machine learning are rapidly expanding fields with increasing relevance in anesthesia and in particular, airway management. The ability of artificial intelligence and machine learning algorithms to recognize patterns from large volumes of complex data makes them attractive for use in pediatric anesthesia airway management. The purpose of this review is to introduce artificial intelligence, machine learning, and deep learning to the pediatric anesthesiologist. Current evidence and developments in artificial intelligence, machine learning and deep learning relevant to pediatric airway management are presented. We critically assess the current evidence on the use of artificial intelligence and machine learning in the assessment, diagnosis, monitoring, procedure assistance, and predicting outcomes during pediatric airway management. Further, we discuss the limitations of these technologies and offer areas for focused research that may bring pediatric airway management anesthesiology into the era of artificial intelligence and machine learning.
Reference Key
matava2019artificialpaediatric Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Matava, Clyde;Pankiv, Evelina;Ahumada, Luis;Weingarten, Benjamin;Simpao, Allan;
Journal paediatric anaesthesia
Year 2019
DOI 10.1111/pan.13792
URL
Keywords

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.