Integrated Retinal Information System for Analyzing Kidney Condition

• Main Author: Perdana, Hatta
• Format: Thesis
• Language: English; English
• Published: 2009
• Subjects: QA76.76 Fuzzy System.
• Online Access: http://etd.uum.edu.my/1571/1/Hatta_Perdana_2009.pdf; http://etd.uum.edu.my/1571/2/1.Hatta_Perdana_2009.pdf; http://etd.uum.edu.my/1571/
• Institution: Universiti Utara Malaysia

Iridology is a science and practice that can express body state based on the analysis of iris structure. The changes or disturbances of disease on body network will be informed by neuron nerve fiber to brain. This energy wave information spread to eye by brain, recorded and fixed by pupil.Then, these recorded fixation become data trails which can be detected by disturbance/disease that is filed by body organ. The research about iridology to analyzing kidney condition has been conducted before using Learning Vector Quantization (LVQ) method. The accuracy is not 100%. In this research, the researcher implements Support Vector Machine(SVM) in classifying the kidney condition to replace LVQ using Matlab R2007b. The accuracy in classifying the kidney condition for right eyes is 100% and for the left eyes is 100% in training set data. If we compared to the accuracy of classification using LVQ, implementing SVM is much better because by implementing LVQ, the accuracy is only 96% for right eyes and only 92% for left eyes.