ArticleEuropean radiology2023
Artificial intelligence vs. radiologist: accuracy of wrist fracture detection on radiographs.
Article in European radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 6 of them syntheses that pooled it.
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Who cites it
33 citing papers in PubMed, 6 syntheses or guidelines pooled it.
- Enhanced fracture detection on radiographs with AI assistance for clinicians: a systematic review and meta-analysis.Annals of medicine · 2026Pooled it
- Diagnostic accuracy of AI-assisted versus independent physician interpretation for bone fractures: a systematic review and meta-analysis.European radiology experimental · 2026Pooled it
- Artificial intelligence software to help detect fractures on X-rays in urgent care: An Early Value Assessment.Health technology assessment (Winchester, England) · 2026Pooled it
- Artificial intelligence in virtual fracture clinics: a systematic review of imaging and clinical-text tools.Journal of orthopaedic surgery and research · 2026Pooled it
- Artificial intelligence in commercial fracture detection products: a systematic review and meta-analysis of diagnostic test accuracy.Scientific reports · 2024Pooled it
- Artificial intelligence for X-ray scaphoid fracture detection: a systematic review and diagnostic test accuracy meta-analysis.European radiology · 2024Pooled it
- Artificial Intelligence Predicts Failure of Nonoperative Treatment in Degenerative Posterosuperior Rotator Cuff Tears.Arthroscopy, sports medicine, and rehabilitation · 2026Article
- Independent bone-level diagnostic accuracy study of an AI tool for detecting appendicular skeletal fractures on radiographs.European radiology · 2026Article
- AI-Assisted Fracture Detection in Orthopedic and Trauma Imaging: Where It Works, Where It Fails, and Principles for Safe Clinical Deployment.Diagnostics (Basel, Switzerland) · 2026Review
- Impact of discrepancies in radiological interpretation on forensic report outcomes: A retrospective study.Ulusal travma ve acil cerrahi dergisi = Turkish journal of trauma & emergency surgery : TJTES · 2026Article
- Advances in Artificial Intelligence for Wrist Joint Injury Diagnosis.International journal of medical sciences · 2026Review
- Novel artificial intelligence model predicts the need for reduction of distal radius fractures.European journal of orthopaedic surgery & traumatology : orthopedie traumatologie · 2025Article
- Review
- Review
- Application of artificial intelligence in the diagnosis of scaphoid fractures: impact of automated detection of scaphoid fractures in a real-life study.La Radiologia medica · 2025Article
- Deep Learning-Based Prediction Model of Surgical Indication of Nasal Bone Fracture Using Waters' View.Diagnostics (Basel, Switzerland) · 2025Article
- Enhancing pediatric distal radius fracture detection: optimizing YOLOv8 with advanced AI and machine learning techniques.BMC medical imaging · 2025Article
- Comparative accuracy of two commercial AI algorithms for musculoskeletal trauma detection in emergency radiographs.Emergency radiology · 2025Article
- Patient Perspectives on Artificial Intelligence in Health Care: Focus Group Study for Diagnostic Communication and Tool Implementation.Journal of participatory medicine · 2025Article
- Cross-validation of an artificial intelligence tool for fracture classification and localization on conventional radiography in Dutch population.Insights into imaging · 2025Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo compare the performances of artificial intelligence (AI) to those of radiologists in wrist fracture detection on radiographs.
methodsThis retrospective study included 637 patients (1917 radiographs) with wrist trauma between January 2017 and December 2019. The AI software used was a deep neuronal network algorithm. Ground truth was established by three senior musculoskeletal radiologists who compared the initial radiology reports (IRR) made by non-specialized radiologists, the results of AI, and the combination of AI and IRR (IR+AI)
resultsA total of 318 fractures were reported by the senior radiologists in 247 patients. Sensitivity of AI (83%; 95% CI: 78-87%) was significantly greater than that of IRR (76%; 95% CI: 70-81%) (p < 0.001). Specificities were similar for AI (96%; 95% CI: 93-97%) and for IRR (96%; 95% CI: 94-98%) (p = 0.80). The combination of AI+IRR had a significantly greater sensitivity (88%; 95% CI: 84-92%) compared to AI and IRR (p < 0.001) and a lower specificity (92%; 95% CI: 89-95%) (p < 0.001). The sensitivity for scaphoid fracture detection was acceptable for AI (84%) and IRR (80%) but poor for the detection of other carpal bones fracture (41% for AI and 26% for IRR).
conclusionsPerformance of AI in wrist fracture detection on radiographs is better than that of non-specialized radiologists. The combination of AI and radiologist's analysis yields best performances. KEY POINTS: • Artificial intelligence has better performances for wrist fracture detection compared to non-expert radiologists in daily practice. • Performance of artificial intelligence greatly differs depending on the anatomical area. • Sensitivity of artificial intelligence for the detection of carpal bones fractures is 56%.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.