Artificial intelligence in Emergency Medical Services dispatching: assessing the potential impact of an automatic speech recognition software on stroke detection taking the Capital Region of Denmark as case in point

Artificial intelligence in Emergency Medical Services dispatching: assessing the potential impact of an automatic speech recognition software on stroke detection taking the Capital Region of Denmark as case in point

Abstract Background and purpose Stroke recognition at the Emergency Medical Services (EMS) impacts the stroke treatment and thus the related health outcome. At the EMS Copenhagen 66.2% of strokes are detected by the Emergency Medical Dispatcher (EMD) and in Denmark approximately 50% of stroke patien...

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Bibliographic Details
Main Authors: Mirjam Lisa Scholz, Helle Collatz-Christensen, Stig Nikolaj Fasmer Blomberg, Simone Boebel, Jeske Verhoeven, Thomas Krafft
Format: Article
Language:English
Published: BMC 2022-05-01
Series:Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine
Subjects:
Artificial intelligence
Emergency Medical Services
Stroke detection
Automated speech recognition
Online Access:https://doi.org/10.1186/s13049-022-01020-6

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