Clinical Studies
Access our extensive library of +40 clinical publications.
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BoneView
Early budget impact analysis of AI to support the review of radiographic examinations for suspected fractures in NHS emergency departments (ED)
Lucy Gregory, Trishal Boodhna, Mathew Storey, Susan Shelmerdine, Alex Novak, David Lowe, Hugh Harvey
ChestView
Efficacy of a deep learning-based software for chest X-ray analysis in an emergency department.
Sathiyamurthy Selvam, Olivier Peyrony, Arben Elezi, Adelia Braganca, Anne-Marie Zagdanski, Lucie Biard, Jessica Assouline, Guillaume Chassagnon, Guillaume Mulier, Constance de Margerie-Mellon
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BoneView
Artificial intelligence and pelvic fracture diagnosis on X-rays: a preliminary study on performance, workflow integration and radiologists’ feedback assessment in a spoke emergency hospital
Rosa F, Buccicardi D, Romano A, Borda F, D’Auria MC, Gastaldo
BoneAge
High performances in bone age estimation using an artificial intelligence solution
Nguyen T, Hermann AL, Ventre J, Ducarouge A, Pourchot A, Marty V et al.
BoneView
A Prospective Approach to Integration of AI Fracture Detection Software in Radiographs into Clinical Workflow
Oppenheimer J, Lüken S, Hamm B, Niehues SM. A
BoneView
To buy or not to buy—evaluating commercial AI solutions in radiology (the ECLAIR guidelines)
Patrick Omoumi, Alexis Ducarouge, Antoine Tournier, Hugh Harvey, Charles E. Kahn Jr, Fanny Louvet-de Verchère, Daniel Pinto Dos Santos, Tobias Kober & Jonas Richiardi
BoneView
Artificial intelligence vs. radiologist: accuracy of wrist fracture detection on radiographs
Cohen M, Puntonet J, Sanchez J, Kierszbaum E, Crema M, Soyer P et al.
BoneView
Assessment of an artificial intelligence aid for the detection of appendicular skeletal fractures in children and young adults by senior and junior radiologists
Nguyen T, Maarek R, Hermann AL, Kammoun A, Marchi A, Khelifi-Touhami MR et al.
BoneView
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
Regnard NE, Lanseur B, Ventre J, Ducarouge A, Clovis L, Lassalle L et al.
BoneView
Added value of an artificial intelligence solution for fracture detection in the radiologist's daily trauma emergencies workflow
Canoni-Meynet L, Verdot P, Danner A, Calame P & Aubry S.
BoneView
Automated detection of acute appendicular skeletal fractures in pediatric patients using deep learning
Hayashi D, Kompel AJ, Ventre J, Ducarouge A, Nguyen T, Regnard NE et al.
BoneView
Improving Radiographic Fracture Recognition Performance and Efficiency Using Artificial Intelligence
Guermazi A, Tannoury C, Kompel AJ, Murakami AM, Ducarouge A, Gillibert A et al.
BoneView
Assessment of an AI Aid in Detection of Adult Appendicular Skeletal Fractures by Emergency Physicians and Radiologists: A Multicenter Cross-sectional Diagnostic Study
Duron L, Ducarouge A, Gillibert A, Lainé J, Allouche C, Cherel N et al.
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