Diabetic Retinopathy is disease of eye that causes injury to the retina and it may ultimately lead to absolute loss of sight. Tests which detect the diabetic retinopathy like visual acuity examination, pupil dilation, and Optical Coherence Tomography (OCT) are time- intense and affects patients too. Fuzzy inference based model allows intelligent system to examine the patient and then infers a conclusion. The proposed fuzzy expert model deploys 9 Input Parameters (Intra ocular pressure, visual field, glucose level in blood, high density lipoprotein, low density lipoprotein, hemoglobin, Glycated sugar, blood pressure and Triglyceride). In this model, expert system recognizes the normal eye, diabetic retinopathy (Severe), diabetic retinopathy (moderate) and diabetic retinopathy (Mild) on the behalf of these 9 Parameters. This technique has efficient low computational cost and has comparative outcomes to those of the ophthalmologist having 88% accuracy.
Fuzzy Expert System, Diabetic Retinopathy, FIS
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