Visionary Cardioscan: Heart Risk Detection Through Retinal Imaging

Heart attacks and hypertension are two cardiovascular disease risk factors that have a major impact on the microvascular system's structure and function. Fundus camera images can detect abnormalities in retinal blood vessels that indicate vascular injury. Using machine learning techniques, preclinical signs of damage, which may not be visible to an observer, can be detected. It proposes a system that uses retinal images to predict heart attack risk. The model leverages vessel segmentation to extract morphological details of retinal blood vessels. The results can assist in identifying heart disease early, especially in young patients.