Abstract: In many parts of the world Diabetic Retinopathy (DR) causes serious problems related to health. There is a need in the medical community system for the early screening of the eye in order to detect the diseases that cause the blindness (Eg: DR). This aided as a motivation for many people who worked on the automated system for the analysis of the retinal images by using the image processing techniques. These features are utilized by the classifiers to grade DR into different stages according to the disease condition and thus indicating the severity. This paper aims at study of the different classifiers that can be used for the grading of DR.
Keywords: Classifiers, Artificial neural network, Support vector machine, test set, training set, Fuzzy logic, Multilayer perceptron, Back propagation algorithm, hidden layers.
Title: A Survey on Different Classifiers for Medical Diagnosis and Grading: Application to Diabetic Retinopathy
Author: Mamatha.B.V, Srilatha L Rao, Deepashree Devaraj, Dr.S.C.Prasanna Kumar
International Journal of Healthcare Sciences
ISSN 2348-5728 (Online)
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