This project explores the use of deep learning in cardiovascular diagnostics by developing a convolutional neural network (CNN) to classify arterial images as “ruptured” or “non-ruptured.” The dataset was self-curated from publicly available images. The model was trained and validated in Google Colab, and training performance was visualized using accuracy and loss plots. This work represents an independent research initiative by a high school student to explore AI applications in cardiology. Future work includes expanding the dataset, improving generalization, and integrating more medically accurate images.Files included:- AI Project Summary.pdf (1-page summary)- Link To AI Model.txt (link to Colab notebook)