ArticleJournal of orthopaedic research : official publication of the Orthopaedic Research Society2017
Predicting early symptomatic osteoarthritis in the human knee using machine learning classification of magnetic resonance images from the osteoarthritis initiative.
Article in Journal of orthopaedic research : official publication of the Orthopaedic Research Society, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers, 2 of them syntheses that pooled it.
What it found
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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
54 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Predictive Value of Machine Learning in Knee Osteoarthritis Progression: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2025Pooled it
- Pooled it
- Evaluation of Pre-Operative Cartilage and Meniscus Ultrashort Echo Time T2* as Biomarkers of Long-Term Clinical Outcomes Following Anterior Cruciate Ligament Reconstruction.Journal of magnetic resonance imaging : JMRI · 2026Article
- Predicting Knee osteoarthritis progression using explainable machine learning and clinical imaging data.Osteoarthritis and cartilage open · 2026Article
- Grading knee cartilage degeneration and meniscal injury with combined ACS-accelerated T1ρ and T2 mapping.BMC medical imaging · 2026Article
- Artificial Intelligence Has Varied Diagnostic and Predictive Performance in Diagnosing Patellofemoral Osteoarthritis, Trochlear Dysplasia, and Patellofemoral Tracking Abnormalities: A Systematic Review.Arthroscopy, sports medicine, and rehabilitation · 2025Review
- The Evolution of Machine Learning and Its Applications in Orthopaedics: A Bibliometric Analysis.Cureus · 2025Review
- Quantitative Evaluation of Tendon Gliding Sounds and Their Classification Using Deep Learning Models.Cureus · 2025Article
- Review
- Potential of AI-based diagnostic grading system for knee osteoarthritis.Frontiers in medicine · 2025Article
- Article
- Assessing the Value of Imaging Data in Machine Learning Models to Predict Patient-Reported Outcome Measures in Knee Osteoarthritis Patients.Bioengineering (Basel, Switzerland) · 2024Article
- ChatGPT Can Offer Satisfactory Responses to Common Patient Questions Regarding Elbow Ulnar Collateral Ligament Reconstruction.Arthroscopy, sports medicine, and rehabilitation · 2024Article
- Machine Learning Models for Prediction of Progression of Knee Osteoarthritis: A Comprehensive Analysis.Journal of pharmacy & bioallied sciences · 2024Article
- Combining enhanced spectral resolution of EMG and a deep learning approach for knee pathology diagnosis.PloS one · 2024Article
- Articular Cartilage-From Basic Science Structural Imaging to Non-Invasive Clinical Quantitative Molecular Functional Information for AI Classification and Prediction.International journal of molecular sciences · 2023Review
- Toward New Assessment of Knee Cartilage Degeneration.Cartilage · 2023Article
- Inverse distance weighting to rapidly generate large simulation datasets.Journal of biomechanics · 2023Article
- Review
- Artificial intelligence and ChatGPT in Orthopaedics and sports medicine.Journal of experimental orthopaedics · 2023Review
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
The purpose of this study is to evaluate the ability of a machine learning algorithm to classify in vivo magnetic resonance images (MRI) of human articular cartilage for development of osteoarthritis (OA). Sixty-eight subjects were selected from the osteoarthritis initiative (OAI) control and incidence cohorts. Progression to clinical OA was defined by the development of symptoms as quantified by the Western Ontario and McMaster Universities Arthritis (WOMAC) questionnaire 3 years after baseline evaluation. Multi-slice T CLINICAL SIGNIFICANCE: Machine learning algorithms applied to T
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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.