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February 19, 2026Radiology2 citations

Impact of Test Set Composition on AI Performance for Pediatric Radiograph Appendicular Skeleton Fracture Detection

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NSNikolaus StrangerMSMario ScherklDSDaniel Stutz

Key Points

  • To evaluate how the composition of test sets impacts the performance of AI in detecting fractures in pediatric radiographs.
  • Analyzed AI performance during fracture detection tasks.
  • Utilized internal test sets with varying image complexity.
  • Measured prediction accuracy and odds of correct predictions against test set composition.
  • Difficult radiographs in the test set correlated with lower prediction accuracy.
  • Odds of correct predictions decreased with more complex images.

Abstract

Artificial intelligence performance in pediatric fracture detection was influenced by test set composition and image complexity, where an internal test set of difficult radiographs was associated with decreased odds of correct predictions.

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Cite This Study

Stranger et al. (2026) studied this question.

synapsesocial.com/papers/6996a869ecb39a600b3ef25ehttps://doi.org/10.1148/radiol.250540
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