Automated Heart Dysfunctionality Identification Based on Iris using Deep Learning

Abstract

One of the most deadly diseases in the world is Heart Disease. The dysfunctionality of the heart at the early stage can be detected using iridology. The study of iridology describes the structure of the human iris as an observation of the condition of organs in the body. In this article, we explore the heart condition through a series of stages such as iris localization, segmentation, extraction of region of interest, histogram equalization and classification using convolutional neural network. The results are evaluated using various quality metrics such as precision, recall, f-score & accuracy.