Diagnostic performance of an AI algorithm for the detection of appendicular bone fractures in pediatric patients.

Journal: European journal of radiology
Published Date: Jul 17, 2024

Abstract

PURPOSE: To evaluate the diagnostic performance of an Artificial Intelligence (AI) algorithm, previously trained using both adult and pediatric patients, for the detection of acute appendicular fractures in the pediatric population on conventional X-ray radiography (CXR).

Authors

  • Paolo Niccolò Franco
    Department of Diagnostic Radiology, Fondazione IRCCS San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, MB, Italy.
  • Cesare Maino
    Department of Radiology, Fondazione IRCCS San Gerardo dei Tintori, Monza 20900, Italy.
  • Ilaria Mariani
    Department of Diagnostic Radiology, Fondazione IRCCS San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, MB, Italy.
  • Davide Giacomo Gandola
    Department of Diagnostic Radiology, Fondazione IRCCS San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, MB, Italy.
  • Davide Sala
  • Marco Bologna
    Department of Electronics, Information and Bioengineering (DEIB), Politecnico Di Milano, Via Golgi 39, 20133, Milan, Italy. marco.bologna@polimi.it.
  • Cammillo Talei Franzesi
    Department of Diagnostic Radiology, Fondazione IRCCS San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, MB, Italy.
  • Rocco Corso
    Department of Diagnostic Radiology, Fondazione IRCCS San Gerardo dei Tintori, Via Pergolesi 33, 20900 Monza, MB, Italy.
  • Davide Ippolito
    Department of Diagnostic and Interventional Radiology, San Gerardo Hospital, Monza, Italy.

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