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Data science is likely to lead to major changes in cardiovascular imaging. Problems with timing, efficiency, and missed diagnoses occur at all stages of the imaging chain. The application of artificial intelligence (AI) is dependent on robust data; the application of appropriate computational approaches and tools; and validation of its clinical application to image segmentation, automated measurements, and eventually, automated diagnosis. AI may reduce cost and improve value at the stages of image acquisition, interpretation, and decision-making. Moreover, the precision now possible with cardiovascular imaging, combined with "big data" from the electronic health record and pathology, is likely to better characterize disease and personalize therapy. This review summarizes recent promising applications of AI in cardiology and cardiac imaging, which potentially add value to patient care.

Original publication

DOI

10.1016/j.jacc.2018.12.054

Type

Journal article

Journal

J Am Coll Cardiol

Publication Date

26/03/2019

Volume

73

Pages

1317 - 1335

Keywords

artificial intelligence, cardiovascular imaging, deep learning, machine learning