An Effective Model for Detection of Dysfunctionality in Heart Based on Iridology using Deep Neural Networks

Abstract

In today’s world heart disease is the primary reason for deaths. WHO has anticipated that 12 million people die every year because of heart diseases. Every organ of the body is represented in the iris in a well-defined manner. The Iris is a micro-structure of the entire body. The abnormality of the heart can be detected using Iridology science. In this article, we examine the heart dysfunctionality through a chain of steps which are localization of iris, segmentation of iris, ROI extraction, histogram equalization of ROI and classification using deep convolutional neural network. The results are assessed based on various standards such as precision, recall, f-score & accuracy.