Artificial Intelligence in Emergency Medicine: Viewpoint of Current Applications and Foreseeable Opportunities and Challenges

• Published in: Journal of medical Internet research Vol. 25; no. 7; p. e40031
• Main Authors: Chenais, Gabrielle, Lagarde, Emmanuel, Gil-Jardiné, Cédric
• Format: Journal Article
• Language: English
• Published: Canada Journal of Medical Internet Research 23.05.2023; Gunther Eysenbach MD MPH, Associate Professor; JMIR Publications
• Subjects: Algorithms; Application; Artificial Intelligence; Clinical outcomes; Computational linguistics; COVID-19; Decision making; Decision support systems; Deep learning; Derivation; Emergency medical care; Emergency Medicine; Emergency services; Ethics; Evidence-based medicine; Health care; Humans; Language processing; Life Sciences; Medicine; Natural language interfaces; Neural networks; Pandemics; Patients; R&D; Research & development; Santé publique et épidémiologie; Technology application; Viewpoint; viewpoint; ethics; emergency medicine; perspectives; mobile phone; artificial intelligence; Ethics; Mobile phone; Perspectives; Artificial intelligence; Viewpoint; Emergency medicine
• ISSN: 1438-8871; 1439-4456; 1438-8871
• DOI: 10.2196/40031

Emergency medicine and its services have reached a breaking point during the COVID-19 pandemic. This pandemic has highlighted the failures of a system that needs to be reconsidered, and novel approaches need to be considered. Artificial intelligence (AI) has matured to the point where it is poised to fundamentally transform health care, and applications within the emergency field are particularly promising. In this viewpoint, we first attempt to depict the landscape of AI-based applications currently in use in the daily emergency field. We review the existing AI systems; their algorithms; and their derivation, validation, and impact studies. We also propose future directions and perspectives. Second, we examine the ethics and risk specificities of the use of AI in the emergency field.