Invasive non invasive cardiovascular imaging. Role of machine learning and artificial intelligence

Cardiovascular imaging has faced a momentous development in the last few decades thanks to refinements in imaging technologies, multimodality integration, and focus on different clinical applications ranging from prevention to diagnosis, prognosis, decision making, and follow-up. These developments equally apply to standard non-invasive imaging modalities, including echocardiography, duplex ultrasound, cardiac magnetic resonance, computed tomography, and nuclear cardiology. Most recently, breakthroughs in data science, machine learning and artificial intelligence have been applied to pre and post-processing of imaging data. This synergy between refined cardiovascular imaging methods and novel computing approaches holds the promise of enhanced diagnostic and prognostic accuracy, as well as improved clinical decision making with an ever increasing focus on individualized cardiovascular care.