A Survey on Risk Assessment of Diabetic Retinopathy using Data Mining Techniques
Keywords:
Data Mining, Artificial neural fuzzy interference system, K-Nearest-Neighbor (KNN), Machine Learning (ML), Principal Component Analysis (PCA).Abstract
One of the serious issue diabetic patients experiences is Diabetic Retinopathy and visual impairment. Since the quantity of diabetes patients is ceaselessly expanding, these outcomes in an increment in the information too. In wellbeing observing diabetes is the regular wellbeing issue these days, which influences people groups. There are different information mining strategies and calculation is utilized for finding the diabetes. Neural Network, Artificial neural fluffy impedance framework, K Nearest-Neighbor (KNN), Genetic Algorithm, Back Propagation calculation and so forth. These systems and the calculations give the better result to the general population and the specialists with respect to the conclusion of the diabetes. There are numerous systems and calculations that assistance to analyze DR in retinal fundus pictures. This paper audits characterizes and thinks about the calculations and procedures recently proposed so as to grow better and progressively compelling calculations.
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