Accuracy of radiologists and radiology residents in detection of paediatric appendicular fractures with and without artificial intelligence.

Journal: BMJ health & care informatics
PMID: 39638562

Abstract

OBJECTIVES: We aim to evaluate the accuracy of radiologists and radiology residents in the detection of paediatric appendicular fractures with and without the help of a commercially available fracture detection artificial intelligence (AI) solution in the hopes of showing potential clinical benefits in a general hospital setting.

Authors

  • Praveen M Yogendra
    Department of Radiology, Sengkang General Hospital, Singapore, Singapore mypraveen@live.com.
  • Adriel Guang Wei Goh
    Department of Radiology, Sengkang General Hospital, Singapore.
  • Sze Ying Yee
    Department of Radiology, Sengkang General Hospital, Singapore.
  • Freda Jawan
    Department of Radiology, Sengkang General Hospital, Singapore, Singapore.
  • Kelvin Kay Nguan Koh
    Department of Radiology, Sengkang General Hospital, Singapore.
  • Timothy Shao Ern Tan
    Department of Diagnostic & Interventional Imaging, KK Women's and Children's Hospital, Singapore, Singapore.
  • Tian Kai Woon
    Department of Diagnostic and Interventional Imaging, KK Women's and Children's Hospital, Singapore, Singapore.
  • Phey Ming Yeap
    Department of Radiology, Sengkang General Hospital, Singapore, Singapore.
  • Min On Tan

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