On Scene Injury Severity Prediction (OSISP) model for trauma developed using the Swedish Trauma Registry.

Journal: BMC medical informatics and decision making
Published Date: Oct 9, 2023

Abstract

BACKGROUND: Providing optimal care for trauma, the leading cause of death for young adults, remains a challenge e.g., due to field triage limitations in assessing a patient's condition and deciding on transport destination. Data-driven On Scene Injury Severity Prediction (OSISP) models for motor vehicle crashes have shown potential for providing real-time decision support. The objective of this study is therefore to evaluate if an Artificial Intelligence (AI) based clinical decision support system can identify severely injured trauma patients in the prehospital setting.

Authors

  • Anna Bakidou
    Department of Electrical Engineering, Chalmers University of Technology, 412 96, Gothenburg, Sweden. bakidou@chalmers.se.
  • Eva-Corina Caragounis
    Department of Surgery, Institute of Clinical Sciences, Sahlgrenska University Hospital, Sahlgrenska Academy, University of Gothenburg, Per Dubbsgatan 15, 413 45, Gothenburg, Sweden.
  • Magnus Andersson Hagiwara
    Center for Prehospital Research, Faculty of Caring Science, Work Life and Social Welfare, University of Borås, 501 90, Borås, Sweden.
  • Anders Jonsson
    Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain.
  • Bengt Arne Sjöqvist
    Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, 412 96, Sweden.
  • Stefan Candefjord
    Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, 412 96, Sweden. stefan.candefjord@chalmers.se.

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