Efforts towards a precision medicine approach in juvenile idiopathic arthritis
Clicks: 1
ID: 324249
2026
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
0.0
/100
1 views
0 readers
AI Quality Assessment
Not analyzed
Readership in this journal
Ranked #154 of 197 articles by views in Lara D. Veeken
Most read
Least read
Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 197 in total.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
Juvenile idiopathic arthritis (JIA) is the commonest group of childhood arthritides. Despite the availability of advanced therapeutics, many children and young people (CYP) with JIA experience disease flares, and in some, chronic joint damage. Tailoring treatment based on unique biological profiles would benefit CYP with JIA given their variable clinical presentation and disease course. To date, biomarkers to predict treatment response are lacking. With advances in single cell technologies, we are now able to profile the genes and proteins of target tissues at unprecedented resolution to define the biological basis of disease and guide novel treatment approaches. The complex analyses and combination of biological and clinical outcome data from large datasets across disease phenotypes have become possible with the development of computational and machine learning methods. Here, we summarise the strategies to integrate data through enable multimodal based approaches to maximise precision medicine and research priorities for CYP with JIA.
| Reference Key |
openalex_W7196929333
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | C Chew, G W Jones, A P Croft, L R Wedderburn, A V Ramanan |
| Journal | Lara D. Veeken |
| Year | 2026 |
| DOI |
10.1093/rheumatology/keag402
|
| URL | |
| Keywords | Keywords not found |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.