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Artificial Intelligence Algorithm for the Interpretation of Traumatic Bone Radiographs

NCT07329881 · Status: ACTIVE_NOT_RECRUITING · Type: OBSERVATIONAL · Enrollment: 500

Last updated 2026-01-09

No results posted yet for this study

Summary

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.

Conditions

  • Trauma (Including Fractures)

Sponsors & Collaborators

  • Hôpital Universitaire Sahloul

    lead OTHER

Principal Investigators

  • Riadh boukef, Pr · Service des urgences CHU Sahloul, Sousse

Eligibility

Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-11-01
Primary Completion
2026-03-30
Completion
2026-03-31

Countries

  • Tunisia

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07329881 on ClinicalTrials.gov