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Original research
Machine learning for outcome predictions of patients with trauma during emergency department care

Authors

  • Joshua David Cardosi Department of Mechanical and Aerospace Engineering, The Ohio State University, Columbus, Ohio, USA PubMed articlesGoogle scholar articles
  • Herman Shen Department of Mechanical and Aerospace Engineering, The Ohio State University, Columbus, Ohio, USA PubMed articlesGoogle scholar articles
  • Jonathan I Groner Center for Pediatric Trauma Research and Center for Injury Research and Policy, Nationwide Children's Hospital, Columbus, Ohio, USADepartment of Surgery, The Ohio State University, Columbus, Ohio, USA PubMed articlesGoogle scholar articles
  • Megan Armstrong Center for Pediatric Trauma Research and Center for Injury Research and Policy, Nationwide Children's Hospital, Columbus, Ohio, USA PubMed articlesGoogle scholar articles
  • Henry Xiang Center for Pediatric Trauma Research and Center for Injury Research and Policy, Nationwide Children's Hospital, Columbus, Ohio, USADepartment of Pediatrics, The Ohio State University, Columbus, Ohio, USA PubMed articlesGoogle scholar articles
  1. Correspondence to Dr Herman Shen; shen.1{at}osu.edu
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Citation

Cardosi JD, Shen H, Groner JI, et al
Machine learning for outcome predictions of patients with trauma during emergency department care
BMJ Health & Care Informatics 2021;28:e100407. doi: 10.1136/bmjhci-2021-100407

Publication history

  • Received May 6, 2021
  • Accepted September 13, 2021
  • First published October 8, 2021.
Online issue publication 
October 08, 2021

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© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. http://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.