SynthesisRMD open2022
Use of machine learning in osteoarthritis research: a systematic literature review.
Synthesis in RMD open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 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
37 citing papers in PubMed.
- Localizing Knee Pain via Explainable Bayesian Generative Models and Counterfactual MRI: Data from the Osteoarthritis Initiative.Journal of imaging informatics in medicine · 2026Article
- Designing machine learning-based models to predict residual pain after functional treatment of acute lateral ankle ligamentous sprains.Journal of orthopaedic surgery and research · 2026Article
- Identification of alkaline phosphatase as a putative biomarker of anti-NGF treatment-associated arthropathies: Machine learning-assisted analyses of clinical trial data.Osteoarthritis and cartilage open · 2026Article
- Novel algorithm for knee localization and diagnosis and grading of knee osteoarthritis based on a priori information: data from OAI.BMC medical imaging · 2026Article
- Molecular Mechanisms of Chondrocyte Hypertrophy Mediated by Physical Cues and Therapeutic Strategies in Osteoarthritis.International journal of molecular sciences · 2026Review
- Implementation of clinical decision support tools for treatment selection in knee osteoarthritis: a scoping review.Therapeutic advances in musculoskeletal disease · 2026Review
- Deep learning-based multiclass classification for the diagnosis of hand arthritis on digital radiography: a multicenter study.Frontiers in medicine · 2026Article
- Machine learning models for clinical and structural knee osteoarthritis prediction: Recent advancements and future directions.Osteoarthritis and cartilage open · 2025Article
- Clinical and molecular landscape of post-traumatic osteoarthritis.Connective tissue research · 2025Review
- Nanoparticle-enabled molecular imaging diagnosis of osteoarthritis.Materials today. Bio · 2025Review
- Estimation of time-to-total knee replacement surgery with multimodal modeling and artificial intelligence.Computers in biology and medicine · 2025Article
- Closed circuit artificial ıntelligence model named morgaf for childhood onset systemic lupus erythematosus diagnosis.Scientific reports · 2025Article
- Screening biomarkers related to cholesterol metabolism in osteoarthritis based on transcriptomics.Scientific reports · 2025Article
- Predictive validity of consensus-based MRI definition of osteoarthritis plus radiographic osteoarthritis for the progression of knee osteoarthritis: A longitudinal cohort study.Osteoarthritis and cartilage open · 2025Article
- A multidimensional approach reveals the function of lactylation related genes in osteoarthritis.Scientific reports · 2025Article
- Artificial intelligence in clinical medicine: a state-of-the-art overview of systematic reviews with methodological recommendations for improved reporting.Frontiers in digital health · 2025Review
- XGBoost-SHAP-based interpretable diagnostic framework for knee osteoarthritis: a population-based retrospective cohort study.Arthritis research & therapy · 2024Article
- Minimally Invasive Therapies for Knee Osteoarthritis.Journal of personalized medicine · 2024Review
- Assessing the Value of Imaging Data in Machine Learning Models to Predict Patient-Reported Outcome Measures in Knee Osteoarthritis Patients.Bioengineering (Basel, Switzerland) · 2024Article
- Identifying significant structural factors associated with knee pain severity in patients with osteoarthritis using machine learning.Scientific reports · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThe aim of this systematic literature review was to provide a comprehensive and exhaustive overview of the use of machine learning (ML) in the clinical care of osteoarthritis (OA).
methodsA systematic literature review was performed in July 2021 using MEDLINE PubMed with key words and MeSH terms. For each selected article, the number of patients, ML algorithms used, type of data analysed, validation methods and data availability were collected.
resultsFrom 1148 screened articles, 46 were selected and analysed; most were published after 2017. Twelve articles were related to diagnosis, 7 to prediction, 4 to phenotyping, 12 to severity and 11 to progression. The number of patients included ranged from 18 to 5749. Overall, 35% of the articles described the use of deep learning And 74% imaging analyses. A total of 85% of the articles involved knee OA and 15% hip OA. No study investigated hand OA. Most of the studies involved the same cohort, with data from the OA initiative described in 46% of the articles and the MOST and Cohort Hip and Cohort Knee cohorts in 11% and 7%. Data and source codes were described as publicly available respectively in 54% and 22% of the articles. External validation was provided in only 7% of the articles.
conclusionThis review proposes an up-to-date overview of ML approaches used in clinical OA research and will help to enhance its application in this field.
Indexed as
Identifiers
What Socratic holds
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 Socratic graph.