Assessment of diabetic retinopathy progression using CNN from ocular thermal images-Reference-Cited by-同舟云学术

Assessment of diabetic retinopathy progression using CNN from ocular thermal images

Published:2023-04-26 Issue: Volume: Page:
ISSN:1432-7643
Container-title:Soft Computing
language:en
Short-container-title:Soft Comput

Author:

Raut Roshani,Sapkal Ashwini,Ingale Vaishali,Borkar Pradnya,Bhanarkar Parul

Publisher

Springer Science and Business Media LLC

Subject

Geometry and Topology,Theoretical Computer Science,Software

Link

https://link.springer.com/content/pdf/10.1007/s00500-023-08238-1.pdf

Reference17 articles.

1. American Academy of Ophthalmology (2023) What is diabetic retinopathy? [Online]. https://www.aao.org/eye-health/diseases/what-is-diabetic-retinopathy

2. Diabetic Retinopathy Detection APTOS Dataset (2023) https://www.kaggle.com/datasets/mariaherrerot/aptos2019. Accessed 8/1/2023.

3. Gangwar AK, Ravi V (2020) Diabetic retinopathy detection using transfer learning and deep learning. Evol Comput Intell 66:679–689

4. Gao Z, Li J, Guo J, Chen Y, Yi Z, Zhong J (2018) Diagnosis of diabetic retinopathy using deep neural networks. IEEE Access J 7:3360–3370

5. Harper CA, Keeffe JE (2012) Diabetic retinopathy management guidelines. Expet Rev Ophthalmol 7(5):417–439

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