This diagnostic study aims to compare the performance of an artificial intelligence (AI) algorithm designed to assist in the interpretation of traumatic bone radiographs (all anatomical regions excluding the thorax) with that of human readers, including emergency medicine and family medicine residents as well as senior physicians (one emergency medicine specialist and one orthopedic surgeon). The study follows a paired reader study design: identical anonymized radiographic images are independently interpreted by the AI system and by human readers. The reference standard ("gold standard") will be defined by the consensus reading of the two senior physicians. Inter-observer agreement (kappa statistics) between the AI, residents, and senior reference readings will be estimated, and false negatives and false positives will be analyzed by lesion type and anatomical location.
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AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
Diagnostic sensitivity and specificity of the AI algorithm compared to human readers
Timeframe: At the end of image interpretation for each reader (expected within 1 month after image collection).