Efficient diabetic retinopathy classification grading using GAN based EM and PCA learning framework
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11042-024-18553-w.pdf
Reference40 articles.
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2. Oh K, Kang HM, Leem D, Lee H, Seo KY, Yoon S (2021) Early detection of diabetic retinopathy based on deep learning and ultra-wide-field fundus images. Sci Rep 11(1):1–9
3. Lois N, CookA J, Wang A, Aldington S, Mistry H, Maredza M, McAuley D et al (2021) Evaluation of a new model of care for people with complications of diabetic retinopathy: The EMERALD Study. Ophthalmology 128(4):561–573
4. Bora A, Balasubramanian S, Babenko B, Virmani S, Venugopalan S, Mitani A, de Oliveira Marinho G et al (2021) Predicting the risk of developing diabetic retinopathy using deep learning. Lancet Digit Health 3(1):e10–e19
5. Tonade D, Timothy Kern S (2021) Photoreceptor cells and RPE contribute to the development of diabetic retinopathy. Prog Retin Eye Res 83:100919
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