Artificial intelligence-assisted diagnosis of glomerular nephritis using a pathological image analysis approach: a multicentre model development and validation study
National Key R&D Program of China, the Key Technologies R&D Program of Guangdong Province, the Guangdong Provincial Clinical Research, the Program of Introducing Talents of Discipline to Universities, the National Natural Science Foundation of China, Eastern Scholars Program from Shanghai Municipal Education Commission and Clinical Research Initiation Plan of Southern Medical University.
Authors
- Nan Jia (ORCID: https://orcid.org/0000-0002-6317-269X)
- Sheng Nie (ORCID: https://orcid.org/0000-0002-8267-7909)
- Haobo Chen (ORCID: https://orcid.org/0000-0002-5378-2697)
- Luhua Jin (ORCID: https://orcid.org/0000-0002-9504-8394)
- Ruixuan Chen (ORCID: https://orcid.org/0000-0001-5042-3982)
- Shiyu Zhou
- Xian Shao (ORCID: https://orcid.org/0000-0003-1720-6788)
- Qi Zhang (ORCID: https://orcid.org/0000-0001-7041-643X)
- Jiao Liu (ORCID: https://orcid.org/0000-0003-0304-241X)
- Fan Luo (ORCID: https://orcid.org/0009-0003-5048-543X)
- Yuewen Sun (ORCID: https://orcid.org/0009-0002-4842-1608)
- Mingzhen Pang
- Jian Geng
- Guobao Wang (ORCID: https://orcid.org/0000-0003-4050-3385)
- Fan Fan Hou
Institutions
- Shanghai University (CN)
- Southern Medical University (CN)
Publication Details
- Journal
- EClinicalMedicine
- Published
- 2025-10-07
- DOI
- https://doi.org/10.1016/j.eclinm.2025.103530
- Citations
- 1
- Primary Topic
- Renal and Vascular Pathologies
- Type
- article
- Field-Weighted Citation Impact
- 1.52