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Heart Attack Prediction via Retinal Imaging by Vancy Fernandes is a document available to read on EtoBox.

What is Heart Attack Prediction via Retinal Imaging about?

This study explores the use of retinal imaging and convolutional neural networks (CNN) to predict heart attack risks non-invasively, achieving approximately 82% accuracy. It emphasizes the importance of early detection of cardiovascular issues through retinal health indicators while addressing ethical considerations in research. The proposed model demonstrates the potential of advanced machine learning techniques in enhancing cardiovascular risk assessment and clinical applications.

Author

Vancy Fernandes

Language

EN