This research is primarily focused on the use of artificial intelligence to analyze genomic data for the use of understanding, diagnosing, and eventually treating polygenic diseases such as polygenic cardiovascular diseases (CVDs). By following the current advances in artificial intelligence through deep learning models, researchers believe that these can be applied to polygenic disease research, to conduct dynamic and complex genomic analyses. Specifically, by combining the computing power of these deep learning models with next-generation sequencing (NGS) technologies, these AI models could find patterns in these diseases’ expression with ease, which could eventually lead to better prognostic guidance, and potentially personalized treatments for these disorders. Researchers believe that through the collusion of clinical data (cardiac imaging, angiography, clinical biomarkers, etc.) with genomic data, further advances can be made in the scientific knowledge on polygenic CVDs.