Cardiovascular disease (CVD), despite the significant advances in the diagnosis and treatments, still represents the leading cause\nof morbidity and mortality worldwide. In order to improve and optimize CVD outcomes, artificial intelligence techniques have\nthe potential to radically change the way we practice cardiology, especially in imaging, offering us novel tools to interpret data and\nmake clinical decisions. AI techniques such as machine learning and deep learning can also improve medical knowledge due to the\nincrease of the volume and complexity of the data, unlocking clinically relevant information. Likewise, the use of emerging\ncommunication and information technologies is becoming pivotal to create a pervasive healthcare service through which elderly\nand chronic disease patients can receive medical care at their home, reducing hospitalizations and improving quality of life. The\naim of this review is to describe the contemporary state of artificial intelligence and digital health applied to cardiovascular\nmedicine as well as to provide physicians with their potential not only in cardiac imaging but most of all in clinical practice.
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