Assessment of an AI Aid in Detection of Adult Appendicular Skeletal Fractures by Emergency Physicians and Radiologists: A Multicenter Cross-sectional Diagnostic Study
Loïc Duron(Inserm), A. Feydy(Université Paris Cité), Elise Lacave(Fondation de Rothschild), André Gillibert(Université de Rouen Normandie), Christian Allouche(Fondation de Rothschild), Aloïs Pourchot(Fondation de Rothschild), Nor-Eddine Regnard(Hôpital Cochin), Nicolas Cherel(Fondation de Rothschild), Nicolas Nitche(Fondation de Rothschild), Alexis Ducarouge(Fondation de Rothschild), Julia Lainé(Assistance Publique – Hôpitaux de Paris), Louis Lassalle(Hôpital Cochin), Zekun Zhang(North China University of Science and Technology), Adrien Felter(Assistance Publique – Hôpitaux de Paris)
Cited by 155
Related Papers
Revolutionizing radiology with GPT-based models: Current applications, future possibilities and limitations of ChatGPT
|Diagnostic and Interventional Imaging|2023|384
How can we combat multicenter variability in MR radiomics? Validation of a correction procedure
|European Radiology|2020|212
Artificial intelligence in diagnostic and interventional radiology: Where are we now?
|Diagnostic and Interventional Imaging|2022|143
Efficacy of Immunotherapy in Patients with Metastatic Mucosal or Uveal Melanoma
|Journal of Oncology|2018|82