Using deep learning and natural language processing models to detect child physical abuse.

Journal: Journal of pediatric surgery
Published Date: Dec 1, 2021

Abstract

BACKGROUND: The recognition of child physical abuse can be challenging and often requires a multidisciplinary assessment. Deep learning models, based on clinical characteristics, laboratory studies, and imaging findings, were developed to facilitate unbiased identification of children who may have been abused.

Authors

  • Niti Shahi
    Division of Pediatric Surgery, Children's Hospital Colorado, Aurora, CO, USA; Department of Surgery, University of Colorado School of Medicine, Aurora, CO, USA; Department of Surgery, University of Massachusetts, Worcester, MA, USA. Electronic address: niti.shahi@umassmemorial.org.
  • Ashwani K Shahi
    Division of Pediatric Surgery, Children's Hospital Colorado, Aurora, CO, USA.
  • Ryan Phillips
    Division of Pediatric Surgery, Children's Hospital Colorado, Aurora, CO, USA; Department of Surgery, University of Colorado School of Medicine, Aurora, CO, USA.
  • Gabrielle Shirek
    Division of Pediatric Surgery, Children's Hospital Colorado, Aurora, CO, USA.
  • Daniel M Lindberg
    Department of Emergency Medicine, University of Colorado School of Medicine, Aurora, CO, USA; Kempe Center for the Prevention and Treatment of Child Abuse and Neglect, University of Colorado School of Medicine, Aurora, CO, USA.
  • Steven L Moulton
    Division of Pediatric Surgery, Children's Hospital Colorado, Aurora, CO, USA; Department of Surgery, University of Colorado School of Medicine, Aurora, CO, USA.

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