ReviewDiagnostics (Basel, Switzerland)2024
Artificial Intelligence-Based Applications for Bone Fracture Detection Using Medical Images: A Systematic Review.
Review in Diagnostics (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
35 citing papers in PubMed, 2 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
- Concerns of Using Large Language Models in Health Care Research and Practice: Umbrella Review.Journal of medical Internet research · 2026Pooled it
- Performance, Heterogeneity, and Methodological Quality of YOLO-Based Models for Fracture Detection: A Systematic Review and Meta-Analysis.Journal of imaging informatics in medicine · 2026Review
- Temporal Reproducibility of Fracture Interpretation in Forensic Radiography: A Multispecialty Comparison of Physicians and Vision Language Models Including Fracture Subtype Description.Tomography (Ann Arbor, Mich.) · 2026Article
- Advances in internal fixation methods for intertrochanteric femoral fractures: A narrative review.Pakistan journal of medical sciences · 2026Review
- The AI implementation gap in trauma radiography: standalone versus discretionary AI-integrated fracture detection.European radiology experimental · 2026Article
- Hip joint image quality screening based on the Diffusion Mamba model.Scientific data · 2026Article
- In silico augmentation strategies for enhanced machine learning performance in fracture recognition.Scientific reports · 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
- Artificial Intelligence in Anterior Cruciate Ligament Tear Diagnosis: A Bibliometric Analysis of the 50 Most Cited Studies.The Indian journal of radiology & imaging · 2026Review
- Artificial Intelligence in Orthopaedics: Clinical Performance, Limitations, and Translational Readiness-A Review.Journal of clinical medicine · 2026Review
- Deep learning and hybrid architectures for atypical and complex bone fracture diagnosis: a systematic review of performance and clinical validity.Frontiers in artificial intelligence · 2026Review
- Advances in Artificial Intelligence for Wrist Joint Injury Diagnosis.International journal of medical sciences · 2026Review
- A lightweight region of interest-level adjudication framework with hard-negative mining and confidence-aware fusion for pediatric fracture detection.Frontiers in artificial intelligence · 2026Article
- Multi-scale feature refinement network for lower limb fracture detection in X-ray images.Frontiers in medicine · 2026Article
- Article
- Surgical Management of Isolated Zygomaticomaxillary Complex Fractures: Role of Objective Morphometric Analysis in Decision-Making.Craniomaxillofacial trauma & reconstruction · 2025Review
- [Artificial intelligence in fracture diagnostics : Potentials and challenges in the clinical practice].Unfallchirurgie (Heidelberg, Germany) · 2025Review
- Attitudes of physical therapists toward AI diagnostics: barriers, enablers, and clinical implications.BMC medical education · 2025Article
- An Overview of Artificial Intelligence Applications in Radiological Imaging for Bone Fracture Diagnosis.Cureus · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
Abstract
Artificial intelligence (AI) is making notable advancements in the medical field, particularly in bone fracture detection. This systematic review compiles and assesses existing research on AI applications aimed at identifying bone fractures through medical imaging, encompassing studies from 2010 to 2023. It evaluates the performance of various AI models, such as convolutional neural networks (CNNs), in diagnosing bone fractures, highlighting their superior accuracy, sensitivity, and specificity compared to traditional diagnostic methods. Furthermore, the review explores the integration of advanced imaging techniques like 3D CT and MRI with AI algorithms, which has led to enhanced diagnostic accuracy and improved patient outcomes. The potential of Generative AI and Large Language Models (LLMs), such as OpenAI's GPT, to enhance diagnostic processes through synthetic data generation, comprehensive report creation, and clinical scenario simulation is also discussed. The review underscores the transformative impact of AI on diagnostic workflows and patient care, while also identifying research gaps and suggesting future research directions to enhance data quality, model robustness, and ethical considerations.
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Registered trials
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.