This paper focuses on using advanced deep learning techniques to analyze fundus iris images for early detection of conditions like glaucoma, diabetes, and heart attacks. By exploiting the unique characteristics of retinal vasculature, the goal is to identify abnormalities that may indicate underlying cardiovascular risk. Our proposed sophisticated deep learning models such as CNNs with Efficient BO, the aim is to improve the accuracy and efficiency of early heart attack detection through noninvasive imaging