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What is ResNet Method for Diabetic Retinopathy Detection about?
This research presents an automated decision-making methodology using a ResNet feed-forward neural network for the detection of diabetic retinopathy (DR) in retinal images. The study analyzes a dataset of 5672 sequential and 7231 non-sequential color fundus and black-and-white images, achieving high accuracy rates of 98.9% for good-quality images and 94.9% for poor-quality images. The proposed methodology aims to enhance early detection of DR, which is crucial for preventing vision loss associated with diab
- Author
- Faiz Rangari
- Language
- EN