Severity Detection of Diabetic Retinopathy Using Deep Learning Algorithms






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Severity Detection of Diabetic Retinopathy Using Deep Learning Algorithms

ANUSHA.M, MANASA.M, PUNITH.H.N, RAHUL.V.SANKA, SARATH.KUMAR.V

ABSTRACT There are several deep literacy ways that are used to perform the prophetic analytics over big data in colorful medical tasks. Prophetic analytics in medical healthcare is a grueling task yet eventually helping the interpreters handle big data- informed timely opinions about case’s medical health and treatment. This paper discusses the prophetic analytics in healthcare. Case’s medical record is attained for experimental exploration. The two infrastructures of deep literacy are enforced. Performance and delicacy of these applied algorithms are enforced and compared. Different deep literacy ways used in this exploration that reveals which algorithm is best suited for the vaticination of diabetes over the case. This paper aims to help croakers and interpreters in early stage to prognosticate diabetic retinopathy using deep literacy ways. Keywords Dataset, ResNet, Convolutional Neural Network.

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