A Study of Early Disease Prediction Using Iridology and Datamining Techniques with Special Reference to Nafld

Abstract

The human iris is a window of healthy human organs. Utilizing iris for disease prediction constitutes iridology. The iris shows variation in its color, texture, shape, and pattern when disease starts to emerge. If an investigation of iris is done, it's possible to predict the disease at the very early stage and save human life. Iridology is typically used as a CAM for examining in many western and European countries. Practitioners of iridology use digital versions of iridoscopes and digital iris cameras to examine the iris, and based on their observations, they recommend remedies to address perceived health issues. Our idea is to use iridology methodology to predict deadly NAFLD. The reason for choosing NAFLD is that nearly 25% of the world population is affected by it, and most of the population is unaware of this disease. Since the lung is a self-regenerating organ, NAFLD is unpredictable and diagnosed only at the later stage of disease where surgery or lung transplantation is the treatment for the patient, which is expensive and survival of the patient is not guaranteed. As iridology reflects the healthy condition of the organs and as NAFLD does not show visible symptom till later stage, iridology will be the best method for its early prediction and treat the person economically with knifeless treatment and guarantees the patient survival with simple medication, regular exercise, and a change in diet. This paper summarizes the methodologies used for various disease early prediction with better accuracy using iridology and also shows that there is more research scope for predicting NAFLD using iridology.