Evidence
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AI-Assisted X-ray Fracture Detection in Residency Training: Evaluation in Pediatric and Adult Trauma Patients
Meetschen, M., Salhöfer L., Beck, N., Kroll, L., Ziegenfu, C. D., Schaarschmidt, B. M., Forsting, M., Mizan, S., Umutlu, S., Hosch, R., Nensa, F. & Haubold, J. -
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AI-based X-ray fracture analysis of the distal radius: accuracy between representative classification, detection and segmentation deep learning models for clinical practice
Russe M. F., Rebmann P., Tran P.H., Kellner E., Reisert M., Bamberg F., Kotter E., Kim S. -
BoneView
Artificial intelligence effectivity in fracture detection
Boginskis V., Zadoroznijs S., Cernavska I., Beikmane D., Sauka J. -
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Artifcial intelligence‐based detection of paediatric appendicular skeletal fractures: performance and limitations for common fracture types and locations
Irmhild Altmann‐Schneider · Christian J. Kellenberger · Sarah‐Maria Pistorius · Camilla Saladin · Debora Schäfer · Nidanur Arslan · Hanna L. Fischer · Michelle Seiler -
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Commercially-available AI algorithm improves radiologists’ sensitivity for wrist and hand fracture detection on X-ray, compared to a CT-based ground truth
Jacques, T., Cardot, N., Ventre, J. et al. -
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Implementing Artificial Intelligence for Emergency Radiology Impacts Physicians' Knowledge and Perception. A Prospective Pre- and Post-Analysis
Hoppe, Boj Friedrich MD; Rueckel, Johannes MD; Dikhtyar, Yevgeniy MD; Heimer, Maurice MD; Fink, Nicola MD; Sabel, Bastian Oliver MD; Ricke, Jens MD; Rudolph, Jan MD; Cyran, Clemens C. MD -
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 -
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A Prospective Approach to Integration of AI Fracture Detection Software in Radiographs into Clinical Workflow
Oppenheimer J, Lüken S, Hamm B, Niehues SM. A