Machine Learning to Diagnose Complications of Diabetes.
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| Title: | Machine Learning to Diagnose Complications of Diabetes. |
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| Authors: | Scheideman AF; Diabetes Technology Society, Burlingame, CA, USA., Shao MM; Diabetes Technology Society, Burlingame, CA, USA., Zelada H; Division of Endocrinology, Diabetes & Metabolism, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, USA., Cuadros J; EyePACS, Inc., Santa Cruz, CA, USA.; Herbert Wertheim School of Optometry & Vision Science, University of California, Berkeley, Berkeley, CA, USA., Foreman J; EyePACS, Inc., Santa Cruz, CA, USA.; Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, Melbourne, VIC, Australia.; Ophthalmology Department of Surgery, University of Melbourne, Melbourne, VIC, Australia., Sarder P; Computational Microscopy Imaging Laboratory, Section of Quantitative Health, Department of Medicine, University of Florida, Gainesville, FL, USA., Ho C; Diabetes Technology Society, Burlingame, CA, USA., Ejskjaer N; Steno Diabetes Center North Denmark and Department of Endocrinology, Aalborg University Hospital, Aalborg, Denmark., Fleischer J; Steno Diabetes Center Zealand, Holbaek, Denmark.; Department of Clinical Medicine, Aarhus University, Aarhus, Denmark., Cichosz SL; Department of Health Science and Technology, Aalborg University, Aalborg, Denmark., Armstrong DG; Keck School of Medicine, University of Southern California, Los Angeles, CA, USA., Mathioudakis N; Division of Endocrinology, Diabetes, and Metabolism, Johns Hopkins University School of Medicine, Baltimore, MD, USA., Wang T; Department of Genetics, Stanford University, Stanford, CA, USA., Tham YC; Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore., Klonoff DC; Diabetes Research Institute, Mills-Peninsula Medical Center (Sutter Health), San Mateo, CA, USA. |
| Source: | Journal of diabetes science and technology [J Diabetes Sci Technol] 2025 Nov; Vol. 19 (6), pp. 1650-1670. Date of Electronic Publication: 2025 Sep 11. |
| Publication Type: | Journal Article; Review |
| Journal Info: | Publisher: Sage Country of Publication: United States NLM ID: 101306166 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1932-2968 (Electronic) Linking ISSN: 19322968 NLM ISO Abbreviation: J Diabetes Sci Technol Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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