Radiologist Performance Study: AI-Assisted Bone Age Assessment Accuracy — Implications for Paediatric Practice
247 Health News Editorial
·18 Apr 2026
·3 min read
·clinical-trialsNew study examines whether AI tools genuinely improve radiologist accuracy in paediatric bone age assessment or if perceived benefits stem from placebo effects. Results could guide evidence-based AI implementation in radiology departments.
Originally reported by ClinicalTrials.gov
References
- 1.Cavallo, F., Mohn, A., Chiarelli, F., & Giannini, C. (2021). Evaluation of bone age in children: a mini-review. Frontiers in Pediatrics, 9, 580314. https://doi.org/10.3389/fped.2021.580314
- 2.Cheng-Hsin General Hospital. (2024). Comparison of the difference in bone age readings among radiologists using artificial intelligence. ClinicalTrials.gov. NCT07121283. https://clinicaltrials.gov/study/NCT07121283
- 3.Halabi, S. S., Prevedello, L. M., Kalpathy-Cramer, J., Mamonov, A. B., Bilbily, A., Cicero, M., Pan, I., Andriole, K. P., Kohli, M. D., Erickson, B. J., & RSNA Pediatric Bone Age Challenge Organizers. (2019). The RSNA pediatric bone age machine learning challenge. Radiology, 290(2), 498-503. https://doi.org/10.1148/radiol.2018180736
- 4.Martin, D. D., Wit, J. M., Hochberg, Z., Sävendahl, L., van Rijn, R. R., Fricke, O., Cameron, N., Caliebe, J., Hertel, T., Kiepe, D., Albertsson-Wikland, K., Thodberg, H. H., Binder, G., & Ranke, M. B. (2011). The use of bone age in clinical practice–part 1. Hormone Research in Paediatrics, 76(1), 1-9. https://doi.org/10.1159/000329372
- 5.Satoh, M. (2015). Bone age: assessment methods and clinical applications. Clinical Pediatric Endocrinology, 24(4), 143-152. https://doi.org/10.1297/cpe.24.143
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247 Health News Editorial
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