Aim: to design an AI based expert system for prediction of diabetic eye morbidity. Method: This research gives a prediction of diabetes retinopathy in diabetic patients using the Articial Intelligence based expert system. This work divided in two parts, rst part is examination of eye vision by the Ophthalmologist and also other examination such as PPBS, Hypotension, Cholesterol, duration of diabetes. Second part is 400 patients medical records are taken in 2019 year. And it is examined in the articial expert system for prediction of diabetes retinopathy. It gives the accuracy, prediction, eye vision threatening, and morbidity in diabetic eye. Result: The articial intelligence expert system has 6 input parameters and in output one parameter which gives the prediction of diabetic neuropathy. The input parameters such as Post Prandial blood sugar, Hemoglobin A1c Test, duration of Diabetes, Hypotension, Cholesterol, and Vision in eyes. The output parameter was the morbidity in diabetic retinopathies which are Non proliferative, Proliferative, CMSE. This system gives accuracy, specicity, prediction of diabetic retinopathy. Conclusion: This system is design for the endocrinologist and ophthalmologist to diagnosis diabetic retinopathy more quickly and prediction of eye morbidity
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