| Issue |
ITM Web Conf.
Volume 74, 2025
International Conference on Contemporary Pervasive Computational Intelligence (ICCPCI-2024)
|
|
|---|---|---|
| Article Number | 01007 | |
| Number of page(s) | 7 | |
| Section | Artificial Intelligence and Machine Learning Applications | |
| DOI | https://doi.org/10.1051/itmconf/20257401007 | |
| Published online | 20 February 2025 | |
Cardiac Risk Assessment Through Retinal Images
1,2,3 Department of CSE, Sreenidhi Institute of Science and Technology, India
4 Department of CSE, Sreenidhi Institute of Science and Technology, India
Cardiovascular disease (CVD) is the leading cause of death across the globe. Therefore, detection at an early stage is all the more crucial. In this project, retinal images captured during a routine eye examination are used for the prediction of heart attack by deep learning and machine learning. Improvement in quality of images, highlights on blood vessels, extracting meaningful features like shape of vessel, and density that relates heart health. The approach will be hybrid, based on a combination of a neural classifier RNN using clustering and AdaBoost for generating highly accurate predictive outputs as well as providing an assessment score for potential issues concerning heart conditions. It is a non-invasive cost-effective procedure, fast, easy, and may be conducted along with regular eye checks to encourage early intervention and better health.
Key words: Cardiovascular disease (CVD) / heart attack risk prediction / deep learning / noninvasive screening / eye fundus images / and blood vessel analysis
© The Authors, published by EDP Sciences, 2025
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