IDENTIFICATION OF DECREASE OF ORGAN FUNCTIONAL FUNCTION CONDITION THROUGH IRIS EYE USING THE NEURAL NETWORK METHOD OF LEARNING VECTOR QUANTIZATION

Abstract

One alternative to detect a decrease in the condition of renal organ function in the human body is to use iridology. Usually iridology analysis is done manually by iridology experts. This research was done to create software support module to detect the decreasing condition of kidney organ function in human body using iridology principle. The iris data is processed by extraction of canny edge detection feature to obtain matrix or image vector as artificial neural network input. Methods in the study using artificial neural network learning vector quantization to recognize patterns of kidney organs. Network training results achieved 100% accuracy with training data, while the test achieved 93.75% accuracy with test data. From these results are expected to help detect a decrease in the condition of renal organ function through the iris of the eye.

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