Cross-validation of an artificial intelligence tool for fracture classification and localization on conventional radiography in Dutch population.

Journal: Insights into imaging
Published Date: Jul 3, 2025

Abstract

OBJECTIVES: The aim of this study is to validate the effectiveness of an AI tool trained on Indian data in a Dutch medical center and to assess its ability to classify and localize fractures.

Authors

  • Huibert C Ruitenbeek
    Department of Radiology and Nuclear Medicine, Erasmus MC, University Medical Center, P.O. Box 2040, 3000 CA, Rotterdam, The Netherlands.
  • Sahil Sahil
    Qure.ai, Level 7, Oberoi Commerz II, Goregaon East, Mumbai, India.
  • Aradhana Kumar
    Qure.ai, Level 7, Oberoi Commerz II, Goregaon East, Mumbai, India.
  • Ravi Kumar Kushawaha
    Qure.ai, Level 7, Oberoi Commerz II, Goregaon East, Mumbai, India.
  • Swetha Tanamala
    Qure.ai, Goregaon East, Mumbai, India.
  • Saigopal Sathyamurthy
    Qure.ai Technologies Pvt. Ltd., Floor 2, Prestige Summit, Halasuru, Bangalore, Karnataka, India, 560042 (D.R., S.S., A.K.S., S.A.M., M.T., S.T.).
  • Rohitashva Agrawal
    Qure.ai, Level 7, Oberoi Commerz II, Goregaon East, Mumbai, India.
  • Subhankar Chattoraj
  • Jasika Paramasamy
    Department of Radiology & Nuclear Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands.
  • Daniel Bos
    Department of Radiology and Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
  • Roshan Fahimi
    Department of Radiology, Massachusetts General Hospital and Harvard Medical School, 75 Blossom Court, Suite 248, Boston, MA 02114, United States.
  • Edwin H G Oei
    Department of Radiology & Nuclear Medicine, University Medical Center Rotterdam, Rotterdam, The Netherlands.
  • Jacob J Visser
    Department of Radiology & Nuclear Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands.

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