Machine learning as a supportive tool to recognize cardiac arrest in emergency calls

Stig Nikolaj Blomberg, Fredrik Folke, Annette Kjær Ersbøll, Helle Collatz Christensen, Christian Torp-Pedersen, Michael R Sayre, Catherine R Counts, Freddy K Lippert

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

1 Citation (Scopus)
16 Downloads (Pure)
OriginalsprogEngelsk
TidsskriftResuscitation
Vol/bind138
Sider (fra-til)322-329
Antal sider8
ISSN0300-9572
DOI
StatusUdgivet - maj 2019

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Heart Arrest
Out-of-Hospital Cardiac Arrest
Emergencies
Machine Learning
Cardiopulmonary Resuscitation
Sensitivity and Specificity
Emergency Medical Dispatcher

Bibliografisk note

Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.

Citer dette

Blomberg, S. N., Folke, F., Kjær Ersbøll, A., Collatz Christensen, H., Torp-Pedersen, C., Sayre, M. R., ... Lippert, F. K. (2019). Machine learning as a supportive tool to recognize cardiac arrest in emergency calls. Resuscitation, 138, 322-329. https://doi.org/10.1016/j.resuscitation.2019.01.015
Blomberg, Stig Nikolaj ; Folke, Fredrik ; Kjær Ersbøll, Annette ; Collatz Christensen, Helle ; Torp-Pedersen, Christian ; Sayre, Michael R ; Counts, Catherine R ; Lippert, Freddy K. / Machine learning as a supportive tool to recognize cardiac arrest in emergency calls. I: Resuscitation. 2019 ; Bind 138. s. 322-329.
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title = "Machine learning as a supportive tool to recognize cardiac arrest in emergency calls",
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author = "Blomberg, {Stig Nikolaj} and Fredrik Folke and {Kj{\ae}r Ersb{\o}ll}, Annette and {Collatz Christensen}, Helle and Christian Torp-Pedersen and Sayre, {Michael R} and Counts, {Catherine R} and Lippert, {Freddy K}",
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year = "2019",
month = "5",
doi = "10.1016/j.resuscitation.2019.01.015",
language = "English",
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Blomberg, SN, Folke, F, Kjær Ersbøll, A, Collatz Christensen, H, Torp-Pedersen, C, Sayre, MR, Counts, CR & Lippert, FK 2019, 'Machine learning as a supportive tool to recognize cardiac arrest in emergency calls', Resuscitation, bind 138, s. 322-329. https://doi.org/10.1016/j.resuscitation.2019.01.015

Machine learning as a supportive tool to recognize cardiac arrest in emergency calls. / Blomberg, Stig Nikolaj; Folke, Fredrik; Kjær Ersbøll, Annette; Collatz Christensen, Helle; Torp-Pedersen, Christian; Sayre, Michael R; Counts, Catherine R; Lippert, Freddy K.

I: Resuscitation, Bind 138, 05.2019, s. 322-329.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

TY - JOUR

T1 - Machine learning as a supportive tool to recognize cardiac arrest in emergency calls

AU - Blomberg, Stig Nikolaj

AU - Folke, Fredrik

AU - Kjær Ersbøll, Annette

AU - Collatz Christensen, Helle

AU - Torp-Pedersen, Christian

AU - Sayre, Michael R

AU - Counts, Catherine R

AU - Lippert, Freddy K

N1 - Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.

PY - 2019/5

Y1 - 2019/5

KW - Artificial intelligence

KW - Cardiopulmonary resuscitation

KW - Detection time

KW - Dispatch-assisted cardiopulmonary resuscitation

KW - Emergency medical services

KW - Machine learning

KW - Out-of-hospital cardiac arrest

UR - http://www.scopus.com/inward/record.url?scp=85060455459&partnerID=8YFLogxK

U2 - 10.1016/j.resuscitation.2019.01.015

DO - 10.1016/j.resuscitation.2019.01.015

M3 - Journal article

VL - 138

SP - 322

EP - 329

JO - Resuscitation

JF - Resuscitation

SN - 0300-9572

ER -