Assessing AI-Supported Fracture Detection in Emergency Care Units

Brief Summary The purpose of this study is to determine if artificial intelligence (AI) can assist doctors in detecting broken bones, effusions, dislocations and bone lesions more quickly and accurately in an emergency room setting. The study will also evaluate whether AI can save time and reduce costs in healthcare. The main questions to be addressed are: * Does AI improve the accuracy of detecting broken bones/dislocations/effusions/bone lesions? * Can AI expedite the process of diagnosing broken bones/dislocations/effusions/bone lesions? * Does AI reduce healthcare costs by enhancing efficiency? To investigate these questions, two groups of patients will be compared. One group will follow the traditional diagnostic approach, while the other group will utilize AI to assist in diagnosing X-rays. Participants in the study will: Undergo standard X-ray imaging of injured arms or legs, as part of routine care. Have X-rays reviewed by doctors with or without AI support, depending on the assigned group. The study will include patients of all ages presenting to the emergency room with an isolated injury or joint complaints. No additional tests or treatments beyond standard care will be involved.

NCT Number	NCT06754137
Lead Sponsor	Salzburger Landeskliniken Collaborators: Klinikum Nürnberg
Conditions	Fractures, Bone, Effusion Joint, Bone Lesion, Dislocation
Enrollment	4,800 participants
Start Date	2025-03-31
Primary Completion	2026-04-30 (estimated)
Study Completion	2026-04-30 (estimated)
Updated on ClinicalTrials.gov	2026-01-22