Peer-reviewed publications
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- Paediatrics, RBfracture
RBfracture achieved a sensitivity of 92%, specificity of 83%, and overall accuracy of 87%. When supported by RBfracture, radiology residents improved across all metrics—sensitivity increased from 84% to 87%, specificity from 91% to 92%, and diagnostic accuracy from 88% to 90%. The algorithm performed consistently well in children under and over the age of five, with no significant drop in performance.
- Paediatrics, RBfracture
RBfracture demonstrated the highest standalone performance, with 97% accuracy and 97% sensitivity. Both junior and senior readers improved their diagnostic accuracy when supported by RBfracture. Notably, the AI successfully detected six subtle fractures that were missed by all human readers, highlighting its value in enhancing clinical decision-making.
- RBfracture
RBfracture demonstrated a sensitivity of 98.9% and an accuracy of 85.9%, showing near-perfect agreement with the reference standard. Its implementation highlights significant potential for reducing costs, saving time, and easing manpower demands. By minimizing missed diagnoses, RBfracture helps prevent delays in treatment for patients and reduces the need for callbacks, ultimately supporting more efficient emergency care.
- RBfracture
Using RBfracture improved diagnostic performance, increasing sensitivity from 72% to 80% and specificity from 81% to 85%. This led to a 29% relative reduction in missed fractures, with the most notable improvement seen in detecting nonobvious fractures, where sensitivity rose from 60% to 71%.
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