Iridology based Vital Organs Malfunctioning identification using Machine learning Techniques

Abstract

This paper proposes a non-invasive method based on computerized iridology that can identify the malfunctioning of vital organs like the heart, lung and pancreas. Data of 100 patients suffering either from diabetes, heart disease or lung disease is collected. The data is used to develop an algorithm that can identify vital organ malfunctioning based on iridology. Measures like accuracy, error rate, precision, recall, specificity and F-measure are applied on the algorithm for evaluation. The results show an accuracy of 0.9166, which shows the effectiveness of the proposed algorithm.

Keywords-Iridology, diabetes, heart disease, lung disease.