Abstract
A thorough investigation is conducted in this work to identify diabetic retinopathy using retinal fundus images. Diabetes affects the retinal blood vessels in the interior of the eye, causing diabetic retinopathy, an eye disorder. In working population, diabetic retinopathy is very common major root of sight loss or blindness. If this illness is not identified in its early stages, it may cause permanent eyesight loss. The rate of damage can be reduced or avoided if it is predicted in advance. Utilising deep learning approaches for the automatic detection and prediction of diabetic retinopathy, recent developments in AI-assisted disease diagnosis have yielded positive and reliable results. By using deep learning algorithms, we can increase accuracy compared to prior machine learning methods.
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Chandankhede, M., Zade, A. (2024). Deep Learning Methods for Predicting Severity for Diabetic Retinopathy on Retinal Fundus Images. In: Gunjan, V.K., Kumar, A., Zurada, J.M., Singh, S.N. (eds) Computational Intelligence in Machine Learning. ICCIML 2022. Lecture Notes in Electrical Engineering, vol 1106. Springer, Singapore. https://doi.org/10.1007/978-981-99-7954-7_4
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DOI: https://doi.org/10.1007/978-981-99-7954-7_4
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