Evidence

Driving adoption with strong scientific evidence

  • Toan Nguyen,
  • Pediatric Radiology

Assessment of an artificial intelligence aid for the detection of appendicular skeletal fractures in children and young adults by senior and junior radiologists

BoneView
  • Regnard et. al,
  • European Journal of Radiology

Assessment of performances of a deep learning algorithm for the detection of limbs and pelvic fractures, dislocations, focal bone lesions, and elbow effusions on trauma X-rays

BoneView
  • Canoni-Meynet et. al,
  • Diagnostic and Interventional Imaging

Added value of an artificial intelligence solution for fracture detection in the radiologist’s daily trauma emergencies workflow

BoneView
  • Nguyen et. al,
  • ESPR 2022

Deep learning algorithm to predict Greulich and Pyle bone age

BoneView
  • Hayashi et. al,
  • Skeletal Radiology

Automated detection of acute appendicular skeletal fractures in pediatric patients using deep learning

ChestView
  • Bennani et. al,
  • ESTI 2022

Evaluation of radiologists’ performance compared to a deep learning algorithm for the detection of thoracic abnormalities on chest X-ray

ChestView
  • Bennani et. al,
  • ECR 2022

Evaluation of radiologists’ performance compared to a deep learning algorithm for the detection of thoracic abnormalities on chest X-ray

BoneView
  • Ali Guermazi ,
  • Radiology

Improving Radiographic Fracture Recognition Performance and Efficiency Using Artificial Intelligence

BoneView
  • ECR 2022

Artificial Intelligence (AI) support for pelvic fracture detection on plain radiographs: a preliminary study of AI integration in the clinical workflow

BoneView
  • Maarek et. al,
  • ECR 2022

Assessment of an AI aid in detection of pediatric appendicular skeletal fractures by senior and junior radiologists.

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