ReviewArthritis research & therapy2022
Artificial intelligence and the future of radiographic scoring in rheumatoid arthritis: a viewpoint.
Review in Arthritis research & therapy, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
19 citing papers in PubMed, 2 syntheses or guidelines pooled it, 39 citations in OpenAlex.
- Rheumatoid Arthritis referral criteria: systematic review of the literature.BMC rheumatology · 2026Pooled it
- Mechanistic role of quercetin as inhibitor for adenosine deaminase enzyme in rheumatoid arthritis: systematic review.Cellular & molecular biology letters · 2024Pooled it
- Synovial microenvironment and fluorescence imaging for early rheumatoid arthritis diagnosis.Journal of pharmaceutical analysis · 2026Review
- Targeting NAV2-mediated Wnt/β-catenin signaling in rheumatoid arthritis: current evidence and emerging therapeutic approaches.Molecular biology reports · 2026Review
- Comparative evaluation of large language model-based AI platforms for radiographic assessment in rheumatoid arthritis.Rheumatology international · 2026Article
- Global variation in the quality of care for rheumatoid arthritis and associated factors.Arthritis research & therapy · 2026Article
- Comparative evaluation of large language models on multiple-choice and image-based rheumatology questions.Rheumatology international · 2025Article
- Review
- Bibliometric analysis of the application of artificial intelligence in orthopedic imaging.Quantitative imaging in medicine and surgery · 2025Article
- Deep learning enables automatic detection of joint damage progression in rheumatoid arthritis-model development and external validation.Rheumatology (Oxford, England) · 2025Article
- Multistage deep learning methods for automating radiographic sharp score prediction in rheumatoid arthritis.Scientific reports · 2025Article
- 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
- Can eye-tracking help to create a new method for X-ray analysis of rheumatoid arthritis patients, including joint segmentation and scoring methods?PLOS digital health · 2024Article
- Application of artificial intelligence in rheumatic disease: a bibliometric analysis.Clinical and experimental medicine · 2024Article
- Development of a deep learning model for automated detection of calcium pyrophosphate deposition in hand radiographs.Frontiers in medicine · 2024Article
- RANet: a custom CNN model and quanvolutional neural network for the automated detection of rheumatoid arthritis in hand thermal images.Scientific reports · 2023Article
- ChatGPT: when artificial intelligence replaces the rheumatologist in medical writing.Annals of the rheumatic diseases · 2023Article
- Therapeutic potential of Coptis chinensis for arthritis with underlying mechanisms.Frontiers in pharmacology · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Rheumatoid arthritis is an autoimmune condition that predominantly affects the synovial joints, causing joint destruction, pain, and disability. Historically, the standard for measuring the long-term efficacy of disease-modifying antirheumatic drugs has been the assessment of plain radiographs with scoring techniques that quantify joint damage. However, with significant improvements in therapy, current radiographic scoring systems may no longer be fit for purpose for the milder spectrum of disease seen today. We argue that artificial intelligence is an apt solution to further improve upon radiographic scoring, as it can readily learn to recognize subtle patterns in imaging data to not only improve efficiency, but can also increase the sensitivity to variation in mild disease. Current work in the area demonstrates the feasibility of automating scoring but is yet to take full advantage of the strengths of artificial intelligence. By fully leveraging the power of artificial intelligence, faster and more sensitive scoring could enable the ongoing development of effective treatments for patients with rheumatoid arthritis.
Indexed as
Identifiers
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.