ArticleClinical rheumatology2020
Detection of rheumatoid arthritis from hand radiographs using a convolutional neural network.
Article in Clinical rheumatology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.
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Who cites it
35 citing papers in PubMed, 87 citations in OpenAlex.
- Radiograph-Based Deep Learning Model to Support Finger Joint Selection for Ultrasound Examination in Rheumatoid Arthritis.Diagnostics (Basel, Switzerland) · 2026Article
- Radiographic Bone Texture Analysis using Deep Learning Models for Early Rheumatoid Arthritis Diagnosis.Journal of imaging informatics in medicine · 2026Article
- Artificial intelligence in the diagnosis and assessment of damage in peripheral inflammatory arthritis: a scoping review.Therapeutic advances in musculoskeletal disease · 2026Article
- Automated Diagnosis of Rheumatoid Arthritis From Hand Radiographs Using Artificial Intelligence: A Retrospective Study.Clinical medicine insights. Arthritis and musculoskeletal disorders · 2026Article
- What's New in Hand Surgery: Transformative advancements and Emerging Trends.Orthopedic reviews · 2026Article
- Deep learning analysis for rheumatologic imaging: current trends, future directions, and the role of human.Journal of rheumatic diseases · 2025Review
- Current application, possibilities, and challenges of artificial intelligence in the management of rheumatoid arthritis, axial spondyloarthritis, and psoriatic arthritis.Therapeutic advances in musculoskeletal disease · 2025Review
- Deep Learning Classification of Rheumatoid Arthritis in Hand Radiographs Interpretability Insights and Web Application.ImmunoTargets and therapy · 2025Article
- Physician practices in referring rheumatoid hand and thumb carpometacarpal arthritis cases to hand surgeons.Saudi medical journal · 2024Article
- Radiograph-based rheumatoid arthritis diagnosis via convolutional neural network.BMC medical imaging · 2024Article
- Deep learning in rheumatological image interpretation.Nature reviews. Rheumatology · 2024Review
- Deep learning discrimination of rheumatoid arthritis from osteoarthritis on hand radiography.Skeletal radiology · 2024Article
- Multi-pose-based convolutional neural network model for diagnosis of patients with central lumbar spinal stenosis.Scientific reports · 2024Article
- Deep Learned Segmentations of Inflammation for Novel ⁹⁹Diagnostics (Basel, Switzerland) · 2023Article
- Artificial intelligence in patient-specific hand surgery: a scoping review of literature.International journal of computer assisted radiology and surgery · 2023Article
- A survey of artificial intelligence in rheumatoid arthritis.Rheumatology and immunology research · 2023Article
- Medical imaging in rheumatoid arthritis: A review on deep learning approach.Open life sciences · 2023Article
- Deep learning-based joint detection in Rheumatoid arthritis hand radiographs.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2023Article
- Artificial intelligence in rheumatoid arthritis: potential applications and future implications.Frontiers in medicine · 2023Review
- Diagnosing growing pains in children by using machine learning: a cross-sectional multicenter study.Medical & biological engineering & computing · 2022Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionPlain hand radiographs are the first-line and most commonly used imaging methods for diagnosis or differential diagnosis of rheumatoid arthritis (RA) and for monitoring disease activity. In this study, we used plain hand radiographs and tried to develop an automated diagnostic method using the convolutional neural networks to help physicians while diagnosing rheumatoid arthritis.
methodsA convolutional neural network (CNN) is a deep learning method based on a multilayer neural network structure. The network was trained on a dataset containing 135 radiographs of the right hands, of which 61 were normal and 74 RA, and tested it on 45 radiographs, of which 20 were normal and 25 RA.
resultsThe accuracy of the network was 73.33% and the error rate 0.0167. The sensitivity of the network was 0.6818; the specificity was 0.7826 and the precision 0.7500.
conclusionUsing only pixel information on hand radiographs, a multi-layer CNN architecture with online data augmentation was designed. The performance metrics such as accuracy, error rate, sensitivity, specificity, and precision state shows that the network is promising in diagnosing rheumatoid arthritis.
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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.