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Accuracy of Diabetic Retinopathy Staging with a Deep Convolutional Neural Network Using Ultra-Wide-Field Fundus Ophthalmoscopy and Optical Coherence Tomography Angiography
PURPOSE: The present study aimed to compare the accuracy of diabetic retinopathy (DR) staging with a deep convolutional neural network (DCNN) using two different types of fundus cameras and composite images. METHOD: The study included 491 ultra-wide-field fundus ophthalmoscopy and optical coherence...
Sparad:
| I publikationen: | J Ophthalmol |
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| Huvudupphovsmän: | , , , , , , , |
| Materialtyp: | Artigo |
| Språk: | Inglês |
| Publicerad: |
Hindawi
2021
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| Ämnen: | |
| Länkar: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8041547/ https://ncbi.nlm.nih.gov/pubmed/33884202 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1155/2021/6651175 |
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