Artificial Intelligence–Assisted Perfusion Density as Biomarker for Screening Diabetic Nephropathy
We aim to study the pathological processes of DR and DN and determine the correspondence between their clinical and pathological manifestations to further clarify the potential of screening DN using AI-assisted UWF PD.
Authors
- Hongyan Wang (ORCID: https://orcid.org/0000-0001-7813-2845)
- Qingjun Zhou (ORCID: https://orcid.org/0000-0002-6109-3445)
- Tingting Liu (ORCID: https://orcid.org/0000-0002-5144-5179)
- Yanfeng Liu (ORCID: https://orcid.org/0009-0003-8252-4288)
- Wenqi Wang (ORCID: https://orcid.org/0000-0003-4053-5088)
- Yanmei Shi (ORCID: https://orcid.org/0000-0001-8038-9703)
- Xiao Xie (ORCID: https://orcid.org/0000-0003-4053-5088)
- Xiaomeng Yuan
- Zhiping Zhang
Institutions
- Shandong University of Traditional Chinese Medicine (CN)
- Jinan Maternity And Care Hospital (CN)
- Shandong Provincial QianFoShan Hospital (CN)
- Shandong Eye Hospital (CN)
- Shandong First Medical University (CN)
Publication Details
- Journal
- Translational Vision Science & Technology
- Published
- 2024-10-10
- DOI
- https://doi.org/10.1167/tvst.13.10.19
- Citations
- 7
- Primary Topic
- Optical Coherence Tomography Applications
- Type
- article
- Field-Weighted Citation Impact
- 1.29