Deep learning–driven immunohistochemical analysis of renal lymphatics for chronic kidney disease: bioinformatic and histopathological study
This clustering-constrained, attention-based weakly supervised framework enables fully automated, reproducible quantification of renal lymphatic vessel density from WSIs, providing renal pathologists with rapid visual and numerical support for diagnosis and risk stratification in CKD and HTN.
Authors
- Yanping Lin (ORCID: https://orcid.org/0000-0001-6260-7666)
- Xin Xu
- Rui Zeng
- Gang Xu
- Guangchang Pei
Institutions
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- Tongji Hospital (CN)
- Huazhong University of Science and Technology (CN)
Publication Details
- Journal
- Journal of Pathology and Translational Medicine
- Published
- 2026-03-13
- DOI
- https://doi.org/10.4132/jptm.2025.12.15
- Primary Topic
- Lymphatic System and Diseases
- Type
- article
- Field-Weighted Citation Impact
- 0.00