Hazel Tang A science writer with data background and an interest in the current affair, culture, and arts; a no-med from an (almost) all-med family. Follow on Twitter.
Dey D, Slomka PJ, Leeson P et al. Artificial Intelligence in Cardiovascular Imaging: JACC State-ofthe-Art Review. J Am Coll Cardiol 2019; 73(11): 1317-1335.
Abstract
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.
The full list of the top 100 articles on artificial intelligence and artificial intelligence in medicine are published here:
Intelligence- Based Medicine
Artificial Intelligence and Human Cognition in Clinical Medicine and Healthcare.
Anthony Chang, MD, MBA, MPH, MS
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