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Correspondence|Articles in Press

The niche of artificial intelligence in trauma and emergency medicine

Published:October 27, 2020DOI:https://doi.org/10.1016/j.ajem.2020.10.050
The niche of artificial intelligence in trauma and emergency medicine
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      Artificial intelligence (AI) can process data into algorithms via pattern recognition and display useful information [
      • Dennis B.M.
      • Stonko D.P.
      • Callcut R.A.
      • et al.
      Artificial neural networks can predict trauma volume and acuity regardless of center size and geography: a multicenter study.
      J Trauma Acute Care Surg. 2019; 87: 181-187https://doi.org/10.1097/TA.0000000000002320
      ,
      • Berlyand Y.
      • Raja A.S.
      • Dorner S.C.
      • et al.
      How artificial intelligence could transform emergency department operations.
      Am J Emerg Med. 2018; 36: 1515-1517https://doi.org/10.1016/j.ajem.2018.01.017
      ,
      • Kang D.Y.
      • Cho K.J.
      • Kwon O.
      • et al.
      Artificial intelligence algorithm to predict the need for critical care in prehospital emergency medical services.
      Scand J Trauma Resusc Emerg Med. 2020; 28 (Published 2020 Mar 4): 17
      https://doi.org/10.1186/s13049-020-0713-4
      ]. In emergency medicine (EM), AI has shown its potential in field triage, within the ED, and after patient discharge [
      • Dennis B.M.
      • Stonko D.P.
      • Callcut R.A.
      • et al.
      Artificial neural networks can predict trauma volume and acuity regardless of center size and geography: a multicenter study.
      J Trauma Acute Care Surg. 2019; 87: 181-187https://doi.org/10.1097/TA.0000000000002320
      ,
      • Berlyand Y.
      • Raja A.S.
      • Dorner S.C.
      • et al.
      How artificial intelligence could transform emergency department operations.
      Am J Emerg Med. 2018; 36: 1515-1517https://doi.org/10.1016/j.ajem.2018.01.017
      ,
      • Kang D.Y.
      • Cho K.J.
      • Kwon O.
      • et al.
      Artificial intelligence algorithm to predict the need for critical care in prehospital emergency medical services.
      Scand J Trauma Resusc Emerg Med. 2020; 28 (Published 2020 Mar 4): 17
      https://doi.org/10.1186/s13049-020-0713-4
      ]. Understanding the current applications and limitations of AI in trauma and EM can expand its utility and function to further patient care and resource allocation. As several studies have demonstrated, AI can process and learn from previous years' data to calculate common periods of high trauma volumes, allowing EDs the advantage of preparation [
      • Dennis B.M.
      • Stonko D.P.
      • Callcut R.A.
      • et al.
      Artificial neural networks can predict trauma volume and acuity regardless of center size and geography: a multicenter study.
      J Trauma Acute Care Surg. 2019; 87: 181-187https://doi.org/10.1097/TA.0000000000002320
      ,
      • Berlyand Y.
      • Raja A.S.
      • Dorner S.C.
      • et al.
      How artificial intelligence could transform emergency department operations.
      Am J Emerg Med. 2018; 36: 1515-1517https://doi.org/10.1016/j.ajem.2018.01.017
      ,
      • Kang D.Y.
      • Cho K.J.
      • Kwon O.
      • et al.
      Artificial intelligence algorithm to predict the need for critical care in prehospital emergency medical services.
      Scand J Trauma Resusc Emerg Med. 2020; 28 (Published 2020 Mar 4): 17
      https://doi.org/10.1186/s13049-020-0713-4
      ]. Amidst the chaos of EM, AI has revealed itself as a potentially invaluable tool in forecasting the impending flow of ED traffic [
      • Dennis B.M.
      • Stonko D.P.
      • Callcut R.A.
      • et al.
      Artificial neural networks can predict trauma volume and acuity regardless of center size and geography: a multicenter study.
      J Trauma Acute Care Surg. 2019; 87: 181-187https://doi.org/10.1097/TA.0000000000002320
      ,
      • Berlyand Y.
      • Raja A.S.
      • Dorner S.C.
      • et al.
      How artificial intelligence could transform emergency department operations.
      Am J Emerg Med. 2018; 36: 1515-1517https://doi.org/10.1016/j.ajem.2018.01.017
      ,
      • Kang D.Y.
      • Cho K.J.
      • Kwon O.
      • et al.
      Artificial intelligence algorithm to predict the need for critical care in prehospital emergency medical services.
      Scand J Trauma Resusc Emerg Med. 2020; 28 (Published 2020 Mar 4): 17
      https://doi.org/10.1186/s13049-020-0713-4
      ].
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      Article Info

      Publication History

      Published online: October 27, 2020
      Accepted: October 20, 2020
      Received in revised form: October 11, 2020
      Received: September 30, 2020

      Publication stage

      In Press Journal Pre-Proof

      Identification

      DOI: https://doi.org/10.1016/j.ajem.2020.10.050

      Copyright

      © 2020 Elsevier Inc. All rights reserved.

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