An Integrated Risk Prediction Model for Gout Using Clinical Data, Ultrasound Features, and Deep Learning: A Retrospective Multicenter Study
A nomogram was constructed based on seven risk predictors (gender, SUA, estimated glomerular filtration rate (eGFR), tophus, bone erosion, DCs, and DL prediction) to predict and quantify gout risk.
Authors
- C Li
- Chunping Ning (ORCID: https://orcid.org/0000-0003-1045-077X)
- Lishan Xiao
- Yizhe Zhao (ORCID: https://orcid.org/0009-0007-8989-0212)
- Mengmeng Yan
- Manhua Liu
- Yuchen Li
- Yongming Liu
Institutions
- Qingdao University (CN)
- Shanghai Jiao Tong University (CN)
- Affiliated Hospital of Qingdao University (CN)
- Qingdao Eighth People's Hospital (CN)
Publication Details
- Journal
- Journal of Inflammation Research
- Published
- 2026-01-01
- DOI
- https://doi.org/10.2147/jir.s543363
- Primary Topic
- Gout, Hyperuricemia, Uric Acid
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Qingdao University
- National Key Research and Development Program of China