Multimodal deep learning improving the accuracy of pathological diagnoses for membranous nephropathy
This multimodal pathological diagnosis system can not only assist pathologists in diagnosing MN rapidly and accurately but also lays the foundation to develop diagnostic models for other glomerular diseases.
Authors
- Tao‐Tao Tang (ORCID: https://orcid.org/0000-0003-0220-3285)
- Siyu Xia
- Jinyue Yang
- Min Kyu Yang (ORCID: https://orcid.org/0000-0002-8006-8405)
- Chiyuan Ma (ORCID: https://orcid.org/0000-0002-1710-5955)
- Qingyang Wei (ORCID: https://orcid.org/0000-0002-7450-5066)
- Jing Huang (ORCID: https://orcid.org/0000-0002-0814-838X)
- Hai-Feng Ni (ORCID: https://orcid.org/0000-0001-8047-6874)
- Kai‐Jie Yu (ORCID: https://orcid.org/0000-0003-3656-8856)
- Yiping Li (ORCID: https://orcid.org/0000-0002-9461-813X)
- Xiuxiu Hu
- Pingsheng Chen (ORCID: https://orcid.org/0000-0002-3876-1994)
- Jiayun Xu
- Yu Zhang (ORCID: https://orcid.org/0000-0002-2172-5540)
- Yuxiang Gong
- Bizhen Wei
Institutions
- Southeast University (BD)
- Zhongda Hospital Southeast University (CN)
- First Affiliated Hospital of Henan University of Science and Technology (CN)
- Southeast University (CN)
Publication Details
- Journal
- Renal Failure
- Published
- 2025-07-14
- DOI
- https://doi.org/10.1080/0886022x.2025.2528106
- Citations
- 3
- Primary Topic
- Systemic Sclerosis and Related Diseases
- Type
- article
- Field-Weighted Citation Impact
- 4.41
Funders
- National Natural Science Foundation of China