ReviewDiagnostics (Basel, Switzerland)2022
Bone Fracture Detection Using Deep Supervised Learning from Radiological Images: A Paradigm Shift.
Review in Diagnostics (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 1 of them a synthesis that pooled it.
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Who cites it
43 citing papers in PubMed, 1 synthesis or guideline pooled it, 155 citations in OpenAlex.
- [Application and prospect of machine learning in orthopaedic trauma].Zhongguo xiu fu chong jian wai ke za zhi = Zhongguo xiufu chongjian waike zazhi = Chinese journal of reparative and reconstructive surgery · 2023Pooled it
- Investigating the Clinical Value in Relation to Implementation and Use of an AI-Generated Fracture Algorithm Tool to Support Clinical Decision-Making.Diagnostics (Basel, Switzerland) · 2026Article
- FAD-MIL: a weakly supervised fracture detection model based on X-ray images.Scientific reports · 2026Article
- Exploring anatomical similarity in zero-shot learning for bone abnormality detection.Scientific reports · 2026Article
- An intelligent segmentation method for leakage points in central serous chorioretinopathy based on fluorescein angiography images.International journal of ophthalmology · 2026Article
- 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
- Enhancing Document Classification Through Multimodal Image-Text Classification: Insights from Fine-Tuned CLIP and Multimodal Deep Fusion.Sensors (Basel, Switzerland) · 2025Article
- The Evolution of Machine Learning and Its Applications in Orthopaedics: A Bibliometric Analysis.Cureus · 2025Review
- Optimizing the power of AI for fracture detection: from blind spots to breakthroughs.Skeletal radiology · 2025Review
- FracFusionNet: A Multi-Level Feature Fusion Convolutional Network for Bone Fracture Detection in Radiographic Images.Diagnostics (Basel, Switzerland) · 2025Article
- Detecting Fifth Metatarsal Fractures on Radiographs Through the Lens of Smartphones: The FIXUS AI Algorithm.Cureus · 2025Article
- Comparative accuracy of two commercial AI algorithms for musculoskeletal trauma detection in emergency radiographs.Emergency radiology · 2025Article
- Automatic Fracture Detection Convolutional Neural Network with Multiple Attention Blocks Using Multi-Region X-Ray Data.Life (Basel, Switzerland) · 2025Article
- Assessing Fracture Detection: A Comparison of Minimal-Resource and Standard-Resource Plain Radiographic Interpretations.Diagnostics (Basel, Switzerland) · 2025Article
- An open source convolutional neural network to detect and localize distal radius fractures on plain radiographs.European journal of trauma and emergency surgery : official publication of the European Trauma Society · 2025Article
- The current landscape of artificial intelligence in oral and maxillofacial surgery- a narrative review.Oral and maxillofacial surgery · 2025Review
- Erroneous Classification and Coding as a Limitation for Big Data Analyses: Causes and Impacts Illustrated by the Diagnosis of Clavicle Injuries.Diagnostics (Basel, Switzerland) · 2025Article
- Novel transfer learning based bone fracture detection using radiographic images.BMC medical imaging · 2025Article
- A multi-module enhanced YOLOv8 framework for accurate AO classification of distal radius fractures: SCFAST-YOLO.Frontiers in medicine · 2025Article
- Enhanced multi-class object detector for bone fracture diagnosis with prescription recommendation.Frontiers in artificial intelligence · 2025Article
Corrections and comments
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Authors and funding
2 authors at 1 institution.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Bone diseases are common and can result in various musculoskeletal conditions (MC). An estimated 1.71 billion patients suffer from musculoskeletal problems worldwide. Apart from musculoskeletal fractures, femoral neck injuries, knee osteoarthritis, and fractures are very common bone diseases, and the rate is expected to double in the next 30 years. Therefore, proper and timely diagnosis and treatment of a fractured patient are crucial. Contrastingly, missed fractures are a common prognosis failure in accidents and emergencies. This causes complications and delays in patients' treatment and care. These days, artificial intelligence (AI) and, more specifically, deep learning (DL) are receiving significant attention to assist radiologists in bone fracture detection. DL can be widely used in medical image analysis. Some studies in traumatology and orthopaedics have shown the use and potential of DL in diagnosing fractures and diseases from radiographs. In this systematic review, we provide an overview of the use of DL in bone imaging to help radiologists to detect various abnormalities, particularly fractures. We have also discussed the challenges and problems faced in the DL-based method, and the future of DL in bone imaging.
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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.