Artificial intelligence and machine learning in emergency medicine

Emergency Medicine Australasia : EMA
Jonathon StewartGirish Dwivedi

Abstract

Interest in artificial intelligence (AI) research has grown rapidly over the past few years, in part thanks to the numerous successes of modern machine learning techniques such as deep learning, the availability of large datasets and improvements in computing power. AI is proving to be increasingly applicable to healthcare and there is a growing list of tasks where algorithms have matched or surpassed physician performance. Despite the successes there remain significant concerns and challenges surrounding algorithm opacity, trust and patient data security. Notwithstanding these challenges, AI technologies will likely become increasingly integrated into emergency medicine in the coming years. This perspective presents an overview of current AI research relevant to emergency medicine.

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Citations

Oct 4, 2019·Journal of the American Medical Informatics Association : JAMIA·Haley S Hunter-ZinckStephan A Gaehde
Nov 30, 2019·Healthcare Informatics Research·Sae Won ChoiKyung Hwan Kim
Dec 13, 2019·Computational and Mathematical Methods in Medicine·Serkan Nas, Melik Koyuncu
Sep 13, 2020·Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine·Pei-I ZhangChien-Cheng Huang
Nov 24, 2020·AI & Society·Tyler L Jaynes
Jan 5, 2021·Journal of the American College of Emergency Physicians Open·Abirami KirubarajanSameer Masood
Apr 21, 2020·Canadian Association of Radiologists Journal = Journal L'Association Canadienne Des Radiologistes·Sabeena JalalSavvas Nicolaou
Jul 11, 2021·Drug Discovery Today·Michel L LeiteFabricio F Costa
Aug 20, 2021·Journal of Medical Systems·Inés Robles MendoFrancisco Martín-Rodríguez
Aug 26, 2021·Emergency Medicine Australasia : EMA·Jonathon E StewartGirish Dwivedi
Nov 7, 2021·Journal of Ultrasound in Medicine : Official Journal of the American Institute of Ultrasound in Medicine·Aaron E KornblithRima Arnaout

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