IJCAT addresses issues of computer applications, information and communication systems, software engineering and management, CAD/CAM/CAE, numerical analysis and simulations, finite element methods and analyses, robotics, computer applications in multimedia and new technologies, computer aided learning and training. Contents: IJCAT is a refereed, international journal, published quarterly, providing an international forum and an authoritative source of information in the field of Computer Applications and related Information Technology.
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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