Fundus Photograph-Derived Computational Features Predict Risk of Cardiovascular Events in the Chronic Renal Insufficiency Cohort Clinical Observational Study.

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Title: Fundus Photograph-Derived Computational Features Predict Risk of Cardiovascular Events in the Chronic Renal Insufficiency Cohort Clinical Observational Study.
Authors: Dhamdhere R; The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, Georgia., Modanwal G; The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, Georgia., Mutha P; The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, Georgia., Medina S; The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, Georgia., Arepalli S; Emory Eye Center, Emory University, Atlanta, Georgia., Rahman M; Division of Nephrology and Hypertension, Department of Medicine, Case Western Reserve University School of Medicine, Cleveland, Ohio., Al-Kindi S; Department of Cardiology, DeBakey Heart and Vascular Center, Houston Methodist, Houston, Texas., Madabhushi A; The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, Georgia.; Atlanta Veterans Affairs Medical Center, Atlanta, Georgia.
Corporate Authors: CRIC Study Investigators
Source: Kidney360 [Kidney360] 2026 Jan 01; Vol. 7 (1), pp. 81-93. Date of Electronic Publication: 2025 Aug 18.
Publication Type: Journal Article
Journal Info: Publisher: Wolters Kluwer Health, Inc. on behalf of the American Society of Nephrology Country of Publication: United States NLM ID: 101766381 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2641-7650 (Electronic) Linking ISSN: 26417650 NLM ISO Abbreviation: Kidney360 Subsets: MEDLINE; In Process
Database: MEDLINE Ultimate
Description
ISSN:2641-7650
DOI:10.34067/KID.0000000955