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- W4313481830 abstract "Abstract Diabetic retinopathy (DR) produces bleeding, exudation, and new blood vessel formation conditions. DR can damage the retinal blood vessels and cause vision loss or even blindness. If DR is detected early, ophthalmologists can use lasers to create tiny burns around the retinal tears to inhibit bleeding and prevent the formation of new blood vessels, in order to prevent deterioration of the disease. Imaging examination is a valuable technique for doctors in the prediction and treatment of diseases. The rapid improvement of deep learning has made image recognition an effective technology; it can avoid misjudgments caused by different doctors’ evaluations and help doctors to predict the condition quickly. Therefore, this paper adopts visualization and preprocessing in the ResNet-50 model to improve module calibration, to enable the model to predict DR accurately." @default.
- W4313481830 created "2023-01-06" @default.
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- W4313481830 date "2023-01-04" @default.
- W4313481830 modified "2023-10-18" @default.
- W4313481830 title "Development of Revised ResNet-50 for Diabetic Retinopathy Detection" @default.
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- W4313481830 doi "https://doi.org/10.21203/rs.3.rs-2200376/v1" @default.
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