ReviewTherapeutic advances in musculoskeletal disease2023
The application of machine learning in early diagnosis of osteoarthritis: a narrative review.
Review in Therapeutic advances in musculoskeletal disease, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis 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
23 citing papers in PubMed, 1 synthesis or guideline pooled it, 39 citations in OpenAlex.
- Predictive Performance of Raman Spectroscopy in Osteoarthritis: A Systematic Review.Journal of medical systems · 2025Pooled it
- Advances in heterogeneity and classification of osteoarthritis.Bone research · 2026Review
- Predicting kinesiophobia in knee osteoarthritis: a head-to-head comparison between machine learning and traditional regression models.BMC musculoskeletal disorders · 2026Article
- Investigating Sex-Linked miRNAs for Potential Osteoarthritis Therapy Biomarkers.International journal of molecular sciences · 2026Article
- Clinical phenotypes and risk stratification for limb-threatening outcomes in acute compartment syndrome: a multicenter externally validated study.Frontiers in artificial intelligence · 2026Article
- Interpretable machine learning integrates multi-source biomarkers for osteoarthritis diagnosis and mechanistic insights: A temporomandibular joint model.Osteoarthritis and cartilage · 2025Article
- Leucine Attenuates Osteoarthritis via mTORC1/LXRα-Mediated Macrophage Reprogramming and Rspo2/β-Catenin Axis Suppression.Cartilage · 2025Article
- Bayesian Graphical Models for Multiscale Inference in Medical Image-Based Joint Degeneration Analysis.Diagnostics (Basel, Switzerland) · 2025Review
- Computational and Imaging Approaches for Precision Characterization of Bone, Cartilage, and Synovial Biomolecules.Journal of personalized medicine · 2025Review
- Biomarker-Guided Imaging and AI-Augmented Diagnosis of Degenerative Joint Disease.Diagnostics (Basel, Switzerland) · 2025Review
- KNN algorithm for accurate identification of IFP lesions in the knee joint: a multimodal MRI study.Scientific reports · 2025Article
- Screening necroptosis genes influencing osteoarthritis development based on machine learning.Scientific reports · 2025Article
- Beyond the Surface: Nutritional Interventions Integrated with Diagnostic Imaging Tools to Target and Preserve Cartilage Integrity: A Narrative Review.Biomedicines · 2025Review
- Exploring the association between circadian rhythms and osteoporosis: new diagnostic and therapeutic targets identified via machine learning.Frontiers in molecular biosciences · 2025Article
- Potential of AI-based diagnostic grading system for knee osteoarthritis.Frontiers in medicine · 2025Article
- A Review for automated classification of knee osteoarthritis using KL grading scheme for X-rays.Biomedical engineering letters · 2025Review
- Development and accuracy of an artificial intelligence model for predicting the progression of hip osteoarthritis using plain radiographs and clinical data: a retrospective study.BMC musculoskeletal disorders · 2024Article
- Article
- [Identification of Osteoarthritis Inflamm-Aging Biomarkers by Integrating Bioinformatic Analysis and Machine Learning Strategies and the Clinical Validation].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2024Article
- Determining rib fracture age from CT scans with a radiomics-based combined model: a multicenter retrospective study.Insights into imaging · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Osteoarthritis (OA) is the commonest musculoskeletal disease worldwide, with an increasing prevalence due to aging. It causes joint pain and disability, decreased quality of life, and a huge burden on healthcare services for society. However, the current main diagnostic methods are not suitable for early diagnosing patients of OA. The use of machine learning (ML) in OA diagnosis has increased dramatically in the past few years. Hence, in this review article, we describe the research progress in the application of ML in the early diagnosis of OA, discuss the current trends and limitations of ML approaches, and propose future research priorities to apply the tools in the field of OA. Accurate ML-based predictive models with imaging techniques that are sensitive to early changes in OA ahead of the emergence of clinical features are expected to address the current dilemma. The diagnostic ability of the fusion model that combines multidimensional information makes patient-specific early diagnosis and prognosis estimation of OA possible in the future.
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What OpenQuestion 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 OpenQuestion graph.