Cardiovascular illness is a primary cause of death and disease globally, highlighting the need for innovative methods in the early assessment of cardiovascular risk and detection. This article examines the latest developments in the domain of artificial intelligence, including deep learning and machine learning, to identify cardiovascular risk. The paper focuses on the use of AI (Artificial intelligence) to analyze various data modalities, specifically highlighting retinal fundus photos as a possible non-invasive risk assessment tool. The paper examines the current state of AI-based cardiovascular disorder detection, emphasizing the difficulties, developments, and potential paths forward in applying these technologies to enhance cardiovascular prediction and facilitate early intervention.