Artificial Intelligence in Cardiovascular Imaging

This review summarizes recent promising applications of artificial intelligence (AI) in cardiology and cardiac imaging, which potentially add value to patient care.

Problems with timing, efficiency, and missed diagnoses occur at all stages of the imaging chain. The application of AI may reduce cost and improve value at all stages of image acquisition, interpretation, and decision-making. The main fields of AI for imaging will pertain to disease phenotyping, diagnostic support, and image interpretation. Grouping of relevant clinical and imaging information with cluster analysis may provide opportunities to better characterize disease. Diagnostic support will be provided by automated image segmentation and automated measurements. The initial steps are being taken towards automated image acquisition and analysis. “Big data” from imaging will interface with high volumes of data from the electronic health record and pathology to provide new insights and opportunities to personalize therapy.