ReviewJournal of clinical medicine2024
Unveiling Artificial Intelligence's Power: Precision, Personalization, and Progress in Rheumatology.
Review in Journal of clinical medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
13 citing papers in PubMed.
- Use of Artificial Intelligence in Rheumatoid Arthritis: Advancements and Novel Perspectives.Journal of clinical medicine · 2026Review
- Clinical-psychosocial archetypes predict short-term outcomes in inflammatory arthritis: an unsupervised segmentation study.Clinical rheumatology · 2026Observational
- Using machine learning to uncover joint involvement patterns linked to disease activity and disability in rheumatoid arthritis.Clinical rheumatology · 2026Article
- Global patterns and predictors of initial treatment in early rheumatoid arthritis: insights from a multinational machine learning study.Clinical rheumatology · 2026Article
- Baseline pain, fatigue, and sleep quality predict 12-week pain improvement in inflammatory arthritis: retrospective real-world analysis of a digital health application cohort.Rheumatology international · 2026Article
- Preferences regarding technology to unobtrusively monitor symptoms in rheumatoid arthritis: a qualitative study using focus group discussions.Rheumatology international · 2025Article
- Review
- Leveraging Artificial Intelligence for the Diagnosis of Systemic Sclerosis Associated Pulmonary Arterial Hypertension: Opportunities, Challenges, and Future Perspectives.Advances in respiratory medicine · 2025Review
- Rethinking arthritis: exploring its types and emerging management strategies.Inflammopharmacology · 2025Review
- Explainable Boosting Machines Identify Key Metabolomic Biomarkers in Rheumatoid Arthritis.Medicina (Kaunas, Lithuania) · 2025Article
- The Inflammatory Link of Rheumatoid Arthritis and Thrombosis: Pathogenic Molecular Circuits and Treatment Approaches.Current issues in molecular biology · 2025Review
- From advanced imaging to molecular insights: the state of the art in omics for axial spondyloarthritis.Therapeutic advances in musculoskeletal disease · 2025Review
- Article
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
This review examines the increasing use of artificial intelligence (AI) in rheumatology, focusing on its potential impact in key areas. AI, including machine learning (ML) and deep learning (DL), is revolutionizing diagnosis, treatment personalization, and prognosis prediction in rheumatologic diseases. Specifically, AI models based on convolutional neural networks (CNNs) demonstrate significant efficacy in analyzing medical images for disease classification and severity assessment. Predictive AI models also have the ability to forecast disease trajectories and treatment responses, enabling more informed clinical decisions. The role of wearable devices and mobile applications in continuous disease monitoring is discussed, although their effectiveness varies across studies. Despite existing challenges, such as data privacy concerns and issues of model generalizability, the compelling results highlight the transformative potential of AI in rheumatologic disease management. As AI technologies continue to evolve, further research will be essential to address these challenges and fully harness the potential of AI to improve patient outcomes in rheumatology.
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.