Comparison of Seven Artificial Intelligence-Assisted Prediction Models for Renal Fibrosis in Chronic Kidney Disease Using Aggregate Index of Systemic Inflammation and Ultrasound Radiomics
The RF-based model effectively evaluates renal fibrosis in CKD patients. Integrating AISI and ultrasound radiomics offers a novel strategy for dynamic assessment and biopsy guidance.
Authors
- Kun Ping Lu (ORCID: https://orcid.org/0000-0002-0734-1567)
- Yixiang Liao (ORCID: https://orcid.org/0000-0002-1277-3938)
- Yutao Wu (ORCID: https://orcid.org/0009-0009-1548-4996)
- Li Wang (ORCID: https://orcid.org/0000-0001-7340-416X)
- Jing Wang (ORCID: https://orcid.org/0000-0002-4979-1902)
- Fei Li (ORCID: https://orcid.org/0000-0002-0532-9054)
- Tao Yang (ORCID: https://orcid.org/0000-0002-7795-6081)
Institutions
- Yangtze University (CN)
- Jingzhou Central Hospital (CN)
- First People's Hospital of Jingzhou (CN)
Publication Details
- Journal
- International Journal of General Medicine
- Published
- 2025-10-01
- DOI
- https://doi.org/10.2147/ijgm.s542130
- Citations
- 1
- Primary Topic
- Renal and Vascular Pathologies
- Type
- article
- Field-Weighted Citation Impact
- 1.52