• Sushant Chavan
• Siddhi Chavan
• Aditi Dhamale
• Maitrayee Divekar
• Akshada Patil

The “Predicting Cardio-vascular Disease Using Retinopathy” project presents a novel approach to cardiovascular health assessment using cutting-edge image analysis methods. This method looks at retinal images (pictures of the back of the eye) to find possible signs of heart attack risk. Heart disease remains a leading cause of illness and death worldwide. Timely detection and evaluation of cardiovascular disease risk are crucial for effective prevention and timely intervention This study looks at how deep learning methods are used to predict cardiovascular risk (CVR) by analyzing retinal images

Retinal Eye Images, Cardiovascular Health, Machine Learning, Deep Learning, Federated Learning, Image Processing, Predictive Modelling, Healthcare Analytics, Cardiovascular Health.

"Cardio Vascular Disease Risk Prediction Using Retinopathy", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 11, page no.b306-b308, November-2024, Available :http://www.jetir.org/papers/JETIR2411137.pdf

"Cardio Vascular Disease Risk Prediction Using Retinopathy", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 11, page no. ppb306-b308, November-2024, Available at : http://www.jetir.org/papers/JETIR2411137.pdf