A systematic review of machine learning and automation in burn wound evaluation: A promising but developing frontier.

Journal: Burns : journal of the International Society for Burn Injuries
PMID: 34419331

Abstract

BACKGROUND: Visual evaluation is the most common method of evaluating burn wounds. Its subjective nature can lead to inaccurate diagnoses and inappropriate burn center referrals. Machine learning may provide an objective solution. The objective of this study is to summarize the literature on ML in burn wound evaluation.

Authors

  • Samantha Huang
    Keck School of Medicine, University of Southern California, Los Angeles, CA, U.S.A.
  • Justin Dang
    Los Angeles County Regional Burn Center, Los Angeles County + University of Southern California Medical Center, Los Angeles, CA, United States.
  • Clifford C Sheckter
    Northern California Regional Burn Center at Santa Clara Valley Medical Center, Division of Plastic & Reconstructive Surgery, Stanford University, Stanford, CA, United States.
  • Haig A Yenikomshian
    Southern California Regional Burn Center at LAC+USC, University of Southern California, Los Angeles, CA.
  • Justin Gillenwater
    Southern California Regional Burn Center at LAC+USC, University of Southern California, Los Angeles, CA.

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