Work

Retinal Image Analysis for Heart Disease Risk Prediction: A Deep Learning Approach

Year: 2025

Type: article

Abstract: Heart disease is considered as one of the leading causes of death worldwide. Predicting heart diseases from retinal fundus images is a promising approach in the early detection and monitoring of cardiovascular health conditions. The change in the retinal microvasculature is an indication towards systemic diseases such as cardiovascular diseases and hypertension. This study aims to explore the potential use of deep learning for early detection and prediction of cardiovascular health. through retinal images. The connection between the heart and the small blood vessels are called microvasculature. Imaging the retinal vessels provides a noninvasive way to study the cardiovascular system. By leveraging the potential of Convolutional Neural Network, retinal images are analyzed to identify patterns and anomalies which strongly correlates with cardiovascular conditions. Experimental results show that our method improves the accuracy in prediction of heart diseases, hence opens a novel and improved non-invasive approach to predict Cardiovascular diseases.

Source: IEEE Access

DOI: 10.1109/access.2025.3562433

Authors: N. D. Bisna, P. Sona, Ajay James

Institutions: APJ Abdul Kalam Technological University, Government Engineering College Thrissur

Language: English

Topic: Retinal Imaging and Analysis

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $2,075