Analyzing pediatric forearm X-rays for fracture analysis using machine learning.

Journal: International journal of computer assisted radiology and surgery
Published Date: Jul 24, 2025

Abstract

PURPOSE: Forearm fractures constitute a significant proportion of emergency department presentations in pediatric population. The treatment goal is to restore length and alignment between the distal and proximal bone fragments. While immobilization through splinting or casting is enough for non-displaced and minimally displaced fractures. However, moderately or severely displaced fractures often require reduction for realignment. However, appropriate treatment in current practices has challenges due to the lack of resources required for specialized pediatric care leading to delayed and unnecessary transfers between medical centers, which potentially create treatment complications and burdens. The purpose of this study is to build a machine learning model for analyzing forearm fractures to assist clinical centers that lack surgical expertise in pediatric orthopedics.

Authors

  • Van Lam
  • Abhijeet Parida
    Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, DC, USA.
  • Sarah Dance
    Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, DC, USA.
  • Sean Tabaie
    Sheikh Zayed Institute for Pediatric Surgical Innovation, Childrens National Hospital, Washington, DC, 20008, USA.
  • Kevin Cleary
  • Syed Muhammad Anwar
    Software Engineering Department, University of Engineering and Technology, Taxila, Pakistan.

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