ReviewWorld journal of orthopedics2021
Machine learning in orthopaedic surgery.
Review in World journal of orthopedics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers, 2 of them syntheses that pooled it.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
55 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- [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
- Neurosurgical skills analysis by machine learning models: systematic review.Neurosurgical review · 2023Pooled it
- Objective Physical Performance Predicts 10-Year Fracture Risk Without Densitometry in Older Men and Women: Development and Head-to-Head Comparison with FRAX in MrOS and SOF.Calcified tissue international · 2026Article
- Capturing the Multiscale Nature of Bone Behavior: Classical, Data-Driven and Hybrid Techniques.Annals of biomedical engineering · 2026Review
- Artificial Intelligence in Orthopaedics: The Future Through the Lens of Knee Surgery.Balkan medical journal · 2026Article
- Artificial intelligence and machine learning: an important new set of tools for clinical shoulder arthroplasty research.JSES international · 2026Review
- Trustworthy AI models to predict prolonged hospital length-of-stay in orthopedic surgery.npj health systems · 2026Article
- Prediction of Clinically Significant Improvement after Lumbar Fusion Surgery Based on Machine Learning.Yonsei medical journal · 2026Article
- Identifying Risk Groups in 401,846 Osteoarthritis Patients Undergoing Total Hip Arthroplasty: A Machine Learning Clustering Analysis.Journal of personalized medicine · 2026Article
- Patient-Level Classification of Rotator Cuff Tears on Shoulder MRI Using an Explainable Vision Transformer Framework.Journal of clinical medicine · 2026Article
- Review
- AI-driven Technologies for Wrist Fracture Prediction: A Narrative Review of Emerging Approaches.Journal of wrist surgery · 2025Article
- Self-supervised learning with BYOL for anterior cruciate ligament tear detection from knee MRI.MethodsX · 2025Article
- Deep learning classification models demonstrate high accuracy and clinical potential in radiograph interpretation in the arthroplasty clinical pathway: A systematic review and meta-analysis.Journal of experimental orthopaedics · 2025Review
- Assessing the accuracy of a machine learning prediction for 2 different shoulder prostheses: an external validation study.JSES international · 2025Article
- Artificial intelligence-based diagnosis of hallux valgus interphalangeus using anteroposterior foot radiographs.World journal of orthopedics · 2025Article
- Artificial Intelligence in Rotator Cuff Tear Detection: A Systematic Review of MRI-Based Models.Diagnostics (Basel, Switzerland) · 2025Review
- Integrating Artificial Intelligence in Orthopedic Care: Advancements in Bone Care and Future Directions.Bioengineering (Basel, Switzerland) · 2025Review
- Development of Machine Learning-based Algorithms to Predict the 2- and 5-year Risk of TKA After Tibial Plateau Fracture Treatment.Clinical orthopaedics and related research · 2025Article
- Comparing prediction accuracy for 30-day readmission following primary total knee arthroplasty: the ACS-NSQIP risk calculator versus a novel artificial neural network model.Knee surgery & related research · 2025Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence and machine learning in orthopaedic surgery has gained mass interest over the last decade or so. In prior studies, researchers have demonstrated that machine learning in orthopaedics can be used for different applications such as fracture detection, bone tumor diagnosis, detecting hip implant mechanical loosening, and grading osteoarthritis. As time goes on, the utility of artificial intelligence and machine learning algorithms, such as deep learning, continues to grow and expand in orthopaedic surgery. The purpose of this review is to provide an understanding of the concepts of machine learning and a background of current and future orthopaedic applications of machine learning in risk assessment, outcomes assessment, imaging, and basic science fields. In most cases, machine learning has proven to be just as effective, if not more effective, than prior methods such as logistic regression in assessment and prediction. With the help of deep learning algorithms, such as artificial neural networks and convolutional neural networks, artificial intelligence in orthopaedics has been able to improve diagnostic accuracy and speed, flag the most critical and urgent patients for immediate attention, reduce the amount of human error, reduce the strain on medical professionals, and improve care. Because machine learning has shown diagnostic and prognostic uses in orthopaedic surgery, physicians should continue to research these techniques and be trained to use these methods effectively in order to improve orthopaedic treatment.
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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.