SynthesisOrthopaedic surgery2025
Artificial Intelligence-Guided Assessment of Femoral Neck Fractures in Radiographs: A Systematic Review and Multilevel Meta-Analysis.
Synthesis in Orthopaedic surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed.
- Trochanteric region fracture classification network (TRFC-net): a deep learning solution to increasing inexperienced residents' trochanteric region fracture classification accuracy on X-rays.Quantitative imaging in medicine and surgery · 2026Article
- Large language models are comparable with commonly used statistical software: A validation of GPT 5.1 for frequentist meta-analysis in orthopaedics.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2026Article
- Convolutional Neural Networks in Radiology: Principles, Clinical Applications, and a Practical Framework for Radiologists.Medical principles and practice : international journal of the Kuwait University, Health Science Centre · 2026Review
- Artificial intelligence-based diagnosis of non-displaced femoral neck fractures shows excellent sensitivity and specificity and reduces the need for computed tomography scans in emergency rooms.Journal of experimental orthopaedics · 2026Article
- Artificial Intelligence in Bone Fracture Detection: A Review of Evidence, Limitations, and Clinical Integration.Cureus · 2025Review
- Comparative accuracy of two commercial AI algorithms for musculoskeletal trauma detection in emergency radiographs.Emergency radiology · 2025Article
- Narrative Review on the Management of Neck of Femur Fractures in People Living with HIV: Challenges, Complications, and Long-Term Outcomes.Microorganisms · 2025Review
- Emerging Diagnostic Approaches for Musculoskeletal Disorders: Advances in Imaging, Biomarkers, and Clinical Assessment.Diagnostics (Basel, Switzerland) · 2025Review
- Artificial intelligence-guided distal radius fracture detection on plain radiographs in comparison with human raters.Journal of orthopaedic surgery and research · 2025Article
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial Intelligence (AI) is a dynamic area of computer science that is constantly expanding its practical benefits in various fields. The aim of this study was to analyze AI-guided radiological assessment of femoral neck fractures by performing a systematic review and multilevel meta-analysis of primary studies. The study protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO) on May 21, 2024 [CRD42024541055]. The updated Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines were strictly followed. A systematic literature search of PubMed, Web of Science, Ovid (Med), and Epistemonikos databases was conducted until May 31, 2024. Critical appraisal using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool showed that the overall quality of the included studies was moderate. In addition, publication bias was presented in funnel plots. A frequentist multilevel meta-analysis was performed using a random effects model with inverse variance and restricted maximum likelihood heterogeneity estimator with Hartung-Knapp adjustment. The accuracy between AI-based and human assessment of femoral neck fractures, sensitivity and specificity with 95% confidence intervals (CIs) were calculated. Study heterogeneity was assessed using the Higgins test I
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Registered trials
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