A machine learning model for diabetic retinopathy risk stratification using routine blood and urine parameters: insights into kidney-eye crosstalk.
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| Title: | A machine learning model for diabetic retinopathy risk stratification using routine blood and urine parameters: insights into kidney-eye crosstalk. |
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| Authors: | Wang Y; Department of Ophthalmology, Affiliated Nantong Clinical College of Nantong University, Nantong First People's Hospital, Nantong, Jiangsu, China.; Department of Ophthalmology, Nantong First People's Hospital, Nantong, China., Yao L; Department of Ophthalmology, Affiliated Nantong Clinical College of Nantong University, Nantong First People's Hospital, Nantong, Jiangsu, China.; Department of Ophthalmology, Nantong First People's Hospital, Nantong, China., Chen T; Medical Research Center, Nantong First People's Hospital, Nantong, China., Zhang Q; Department of Ophthalmology, Affiliated Nantong Clinical College of Nantong University, Nantong First People's Hospital, Nantong, Jiangsu, China.; Department of Ophthalmology, Nantong First People's Hospital, Nantong, China., Cao X; Department of Ophthalmology, Nantong First People's Hospital, Nantong, China., Gu J; Department of Ophthalmology, Nantong First People's Hospital, Nantong, China., Bao S; Department of Ophthalmology, Nantong First People's Hospital, Nantong, China., Chen X; Department of Ophthalmology, Nantong First People's Hospital, Nantong, China., Cao C; Department of Ophthalmology, Nantong First People's Hospital, Nantong, China. |
| Source: | Frontiers in endocrinology [Front Endocrinol (Lausanne)] 2026 Jun 17; Vol. 17, pp. 1843412. Date of Electronic Publication: 2026 Jun 17 (Print Publication: 2026). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Frontiers Research Foundation] Country of Publication: Switzerland NLM ID: 101555782 Publication Model: eCollection Cited Medium: Print ISSN: 1664-2392 (Print) Linking ISSN: 16642392 NLM ISO Abbreviation: Front Endocrinol (Lausanne) Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1664-2392 |
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| DOI: | 10.3389/fendo.2026.1843412 |