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The niche of artificial intelligence in trauma and emergency medicine

Published:October 27, 2020DOI:https://doi.org/10.1016/j.ajem.2020.10.050
      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.
      ,
      • Berlyand Y.
      • Raja A.S.
      • Dorner S.C.
      • et al.
      How artificial intelligence could transform emergency department operations.
      ,
      • 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.
      ]. 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.
      ,
      • Berlyand Y.
      • Raja A.S.
      • Dorner S.C.
      • et al.
      How artificial intelligence could transform emergency department operations.
      ,
      • 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.
      ]. 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.
      ,
      • Berlyand Y.
      • Raja A.S.
      • Dorner S.C.
      • et al.
      How artificial intelligence could transform emergency department operations.
      ,
      • 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.
      ]. 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.
      ,
      • Berlyand Y.
      • Raja A.S.
      • Dorner S.C.
      • et al.
      How artificial intelligence could transform emergency department operations.
      ,
      • 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.
      ].
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