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Machine learning and AI have the potential to change almost every facet of human life; medical imaging and data interpretation is no exception to this rule. This article discusses current and potential uses of machine learning and artificial intelligence in cardiology, diagnostic imaging, and much more, as well as guidance for physicians on critical elements of AI and ML. Based on what it can do, AI is currently in the initial development stages and is divided into two categories, weak and strong AI. The research paper explores the capabilities of ANI, otherwise known as weak AI, in the medical field. Predictive modeling fundamentals important in cardiology are first reviewed, including feature selection and modern implementation of machine learning combined with hard-coded programming. Second, it analyzes several performances in cardiology and relevant disciplines and discusses some of the most popular supervised learning & implementation methods. Third, it shows how unsupervised learning, including deep understanding, may allow precision cardiology and enhance patient outcomes. It presents examples from both general care and cardiovascular medicine as background.