ArticleScientific reports2020
Osteoarthritis of the Temporomandibular Joint can be diagnosed earlier using biomarkers and machine learning.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers, 5 of them syntheses that pooled it.
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The trial behind it
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Who cites it
70 citing papers in PubMed, 5 syntheses or guidelines pooled it, 122 citations in OpenAlex.
- Comparing Traditional Versus AI-Assisted TMJ Disorder Management Approaches: A Systematic Review and Meta-Analysis.Clinical and experimental dental research · 2026Pooled it
- Radiomics-Based Diagnosis in Dentomaxillofacial Radiology: A Systematic Review.Journal of imaging informatics in medicine · 2025Pooled it
- Machine learning-based medical imaging diagnosis in patients with temporomandibular disorders: a diagnostic test accuracy systematic review and meta-analysis.Clinical oral investigations · 2024Pooled it
- Diagnosis of temporomandibular disorders using artificial intelligence technologies: A systematic review and meta-analysis.PloS one · 2022Pooled it
- Machine Learning and Intelligent Diagnostics in Dental and Orofacial Pain Management: A Systematic Review.Pain research & management · 2021Pooled it
- Two-stage deep learning framework for magnetic resonance imaging-based detection of temporomandibular joint osteoarthritis.Oral radiology · 2026Article
- Machine Learning Prediction of Anterior Open-Bite Development After Stabilization Splint Treatment in Temporomandibular Disorder.Clinical and experimental dental research · 2026Article
- Article
- Age-Related Osseous Measures of the Temporomandibular Joint and Mandibular Ramus During Childhood Assessed by Magnetic Resonance Imaging.Orthodontics & craniofacial research · 2026Article
- Automatic Prediction of TMJ Disc Displacement in CBCT Images Using Machine Learning.Journal of imaging informatics in medicine · 2026Article
- Computer-Aided Diagnosis of Equine Temporomandibular Joint Osteoarthritis Using Machine Learning Integrating Computed Tomography Findings and Synovial Fluid Biomarkers.Animals : an open access journal from MDPI · 2026Article
- Ultrasound assessment of temporomandibular disorders: comparative analysis between inflammatory and degenerative patterns in rheumatic and non-rheumatic patients.Clinical rheumatology · 2026Article
- CBCT assisted diagnosis system for temporomandibular joint disc displacement based on deep learning.Progress in orthodontics · 2026Article
- Development and validation of a prognostic prediction model for lumbar-disc herniation based on machine learning and fusion of clinical text data and radiomic features.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026Article
- Clinical decisions in Orthodontics using x-ray-based images and artificial intelligence approaches: a scoping review.Dental press journal of orthodontics · 2026Article
- Interpretable machine learning integrates multi-source biomarkers for osteoarthritis diagnosis and mechanistic insights: A temporomandibular joint model.Osteoarthritis and cartilage · 2025Article
- Predicting risk of early-onset sepsis in low-resource neonatal units using routine healthcare data: development and evaluation of multivariable statistical and machine learning models.BMJ paediatrics open · 2025Article
- Prevalence of degenerative signs of the temporomandibular joint in the Canarian population through the analysis of panoramic radiographs: A pilot study.Journal of clinical and experimental dentistry · 2025Article
- Application of artificial intelligence in the diagnosis and management of temporomandibular joint osteoarthritis using cone-beam computed tomography: An evidence-based systematic review.Imaging science in dentistry · 2025Review
- Toward Precision Diagnosis of Maxillofacial Pathologies by Artificial Intelligence Algorithms: A Systematic Review.Journal of maxillofacial and oral surgery · 2025Review
10 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
18 authors at 4 institutions in 2 countries.
Funding
Abstract
After chronic low back pain, Temporomandibular Joint (TMJ) disorders are the second most common musculoskeletal condition affecting 5 to 12% of the population, with an annual health cost estimated at $4 billion. Chronic disability in TMJ osteoarthritis (OA) increases with aging, and the main goal is to diagnosis before morphological degeneration occurs. Here, we address this challenge using advanced data science to capture, process and analyze 52 clinical, biological and high-resolution CBCT (radiomics) markers from TMJ OA patients and controls. We tested the diagnostic performance of four machine learning models: Logistic Regression, Random Forest, LightGBM, XGBoost. Headaches, Range of mouth opening without pain, Energy, Haralick Correlation, Entropy and interactions of TGF-β1 in Saliva and Headaches, VE-cadherin in Serum and Angiogenin in Saliva, VE-cadherin in Saliva and Headaches, PA1 in Saliva and Headaches, PA1 in Saliva and Range of mouth opening without pain; Gender and Muscle Soreness; Short Run Low Grey Level Emphasis and Headaches, Inverse Difference Moment and Trabecular Separation accurately diagnose early stages of this clinical condition. Our results show the XGBoost + LightGBM model with these features and interactions achieves the accuracy of 0.823, AUC 0.870, and F1-score 0.823 to diagnose the TMJ OA status. Thus, we expect to boost future studies into osteoarthritis patient-specific therapeutic interventions, and thereby improve the health of articular joints.
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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.