Cardiovascular Disease Prediction from Retinal Images using Machine Learning

Abstract

The structure and function of the microvascular are significantly influenced by the key cardiovascular disease risk factors of hypertension and heart attacks. Images taken with a fundus camera can be used to spot irregularities in the blood vessels of retina that indicate the extent injury on blood vessels by hypertension and heart attacks. Using machine learning and AI techniques, detecting the preclinical signs that fall below the threshold of an observer. The proposed methodology aimed to investigate the effects of hypertension and heart attacks on morphological characteristics of retinal blood vessels. With a diagnosis of hypertension and heart attack, data scientists collect retinal images. Interference data is removed— information about structures other than that retinal vasculature using the vessel segmentation method, leaving only morphological details about the blood vessel of retina. Keywords— Heart Disease, Retinal Image, Microvasculature, Hypertension