Evaluation of ultrasound-based predictive models for disease relapse in rheumatoid arthritis patients in clinical remission

The simplified ultrasound-clinical model maintains high predictive accuracy while offering substantially improved clinical feasibility for identifying RA patients at high risk of relapse during clinical remission.

Authors

Institutions

Publication Details

Journal
Quantitative Imaging in Medicine and Surgery
Published
2025-12-31
DOI
https://doi.org/10.21037/qims-2025-1518
Primary Topic
Rheumatoid Arthritis Research and Therapies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Evaluation of ultrasound-based predictive models for disease relapse in rheumatoid arthritis patients in clinical remission

Jiaqi Wei, Y N Li, X F Shen, Fang Nie et al.
Quantitative Imaging in Medicine and Surgery
Rheumatoid Arthritis Research and Therapies
article

Evaluation of ultrasound-based predictive models for disease relapse in rheumatoid arthritis patients in clinical remission

Jiaqi Wei, Y N Li, X F Shen, Fang Nie, Zhen Wang, Yuan Wang, Ting Wang, Yakun Yu
article en

Abstract

The simplified ultrasound-clinical model maintains high predictive accuracy while offering substantially improved clinical feasibility for identifying RA patients at high risk of relapse during clinical remission.

Quantitative Imaging in Medicine and SurgeryVol. 16(1)
Lanzhou University of Technology (CN), Lanzhou University Second Hospital (CN), Lanzhou University (CN)
Good health and well-being
Openalex Percentile: Top 26%
Rheumatoid Arthritis Research and Therapies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.