ReviewRheumatology advances in practice2025
AI for imaging evaluation in rheumatology: applications of radiomics and computer vision-current status, future prospects and potential challenges.
Review in Rheumatology advances in practice, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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
3 citing papers in PubMed.
- The Use of Artificial Intelligence in Improving Diagnostic Modalities in Rheumatoid Arthritis: A Narrative Review.Cureus · 2026Review
- Artificial intelligence in rheumatology: days of a future past.Rheumatology advances in practice · 2025Article
- Incremental diagnostic value of tumor habitat radiomics for risk stratification in thymic epithelial tumors.Frontiers in oncology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Inflammatory rheumatic diseases, a diverse group of immune-mediated conditions, are characterized by chronic inflammation that can lead to irreversible damage to joints, bones and organs, posing a significant global health challenge. If left untreated, these conditions can severely deteriorate patients' quality of life, underscoring the importance of timely and accurate diagnosis and appropriate management. Artificial intelligence (AI), including radiomics and computer vision, presents promising advancements in improving the early diagnosis and monitoring of these diseases through the analysis of various imaging modalities such as X-rays, CT scans, MRIs and ultrasounds. This review examines the current state of AI applications in the imaging analysis of inflammatory rheumatic diseases, including RA, SpA, SS, SSc and GCA. AI has demonstrated encouraging results, achieving high sensitivity, specificity and accuracy, often on par with or exceeding expert performance. The review also highlights future opportunities for improving the diagnosis and management of rheumatic diseases, as well as the challenges associated with their clinical implementation.
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.