Comparison of smartphone-based retinal imaging systems for diabetic retinopathy detection using deep learning-Reference-Cited by-同舟云学术

Comparison of smartphone-based retinal imaging systems for diabetic retinopathy detection using deep learning

Published:2020-07 Issue:S4 Volume:21 Page:
ISSN:1471-2105
Container-title:BMC Bioinformatics
language:en
Short-container-title:BMC Bioinformatics

Author:

Karakaya Mahmut^ORCID,Hacisoftaoglu Recep E.

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Structural Biology

Link

http://link.springer.com/content/pdf/10.1186/s12859-020-03587-2.pdf

Reference22 articles.

1. Aiello LP, Beck RW, Bressler NM, Browning DJ, Chalam KV, Davis M, Ferris IIIFL, Glassman AR, Maturi RK, Stockdale CR, Topping TM. Rationale for the diabetic retinopathy clinical research network treatment protocol for center-involved diabetic macular edema. Ophthalmology. 2011; 118(12):e5–e14.

2. Herman WH. The cost-effectiveness of diabetes prevention: results from the Diabetes Prevention Program and the Diabetes Prevention Program Outcomes Study. Clin Diabetes Endocrinol. 2015; 1:1–9.

3. Hartnett ME, Key IJ, Loyacano NM, Horswell RL, DeSalvo KB. Perceived barriers to diabetic eye care: qualitative study of patients and physicians. Arch Ophthalmol. 2005; 123(3):387–91.

4. Faust O, Acharya R, Ng EYK, Ng KH, Suri JS. Algorithms for the automated detection of diabetic retinopathy using digital fundus images: a review. J Med Syst. 2012; 36(1):145–57.

5. Haddock LJ, Kim DY, Mukai S. Simple, inexpensive technique for high-quality smartphone fundus photography in human and animal eyes. J Ophthalmol. 2013; 2013(518479):5.

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