Development and optimization of AI algorithms for wrist fracture detection in children using a freely available dataset.

Journal: Frontiers in pediatrics
Published Date: Dec 21, 2023

Abstract

INTRODUCTION: In the field of pediatric trauma computer-aided detection (CADe) and computer-aided diagnosis (CADx) systems have emerged offering a promising avenue for improved patient care. Especially children with wrist fractures may benefit from machine learning (ML) solutions, since some of these lesions may be overlooked on conventional X-ray due to minimal compression without dislocation or mistaken for cartilaginous growth plates. In this article, we describe the development and optimization of AI algorithms for wrist fracture detection in children.

Authors

  • Tristan Till
    Department of Applied Computer Sciences, FH JOANNEUM - University of Applied Sciences, Graz, Austria.
  • Sebastian Tschauner
    Division of Pediatric Radiology, Department of Radiology, Medical University of Graz, Graz, Austria.
  • Georg Singer
    Department of Pediatric and Adolescent Surgery, Medical University of Graz, Graz, Austria.
  • Klaus Lichtenegger
    Department of Applied Computer Sciences, FH JOANNEUM - University of Applied Sciences, Graz, Austria.
  • Holger Till
    Department of Pediatric and Adolescent Surgery, Medical University of Graz, Graz, Austria.

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