Automated diabetic retinopathy detection in smartphone-based fundus photography using artificial intelligence
Author:
Publisher
Springer Science and Business Media LLC
Subject
Ophthalmology
Link
http://www.nature.com/articles/s41433-018-0064-9.pdf
Reference22 articles.
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2. Namperumalswamy P, Nirmalan PK, Ramaswamy KM. Developing a screening program to detect sight threatening retinopathy in south India. Diabetes Care. 2003;26:1831–5.
3. Ryan ME, Rajalakshmi R, Prathiba V, Anjana RM, Ranjani H, VenkatNarayan KM, et al. Comparison Among Methods of Retinopathy Assessment (CAMRA) study: smartphone, nonmydriatic, and mydriatic photography. Ophthalmology. 2015;122:2038–43.
4. Rajalakshmi R, Arulmalar S, Usha M, Prathiba V, Kareemuddin KS, Anjana RM, et al. Validation of smartphone based retinal photography for diabetic retinopathy screening. PLoS ONE. 2015;10:e0138285.
5. Russo A, Morescalchi F, Costagliola C, Delcassi L, Semeraro F. Comparison of smartphone ophthalmoscopy with slit-lamp biomicroscopy for grading diabetic retinopathy. Am J Ophthalmol. 2015;159:360–4.e1.
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