Review ArticlesArtificial Intelligence Pertaining to Cardiothoracic Imaging and Patient Care Beyond Image InterpretationMoore, William MD; Ko, Jane MD; Gozansky, Elliott MD, PhDAuthor Information NYU Langone Health, New York, NY The authors declare no conflicts of interest. Correspondence to: William Moore, MD, NYU Langone Health, 660 1st Avenue, 3rd Floor, New York, NY 10016 (e-mail: firstname.lastname@example.org). Journal of Thoracic Imaging: May 2020 - Volume 35 - Issue 3 - p 137-142 doi: 10.1097/RTI.0000000000000486 Buy Metrics Abstract Artificial intelligence (AI) is a broad field of computational science that includes many subsets. Today the most widely used subset in medical imaging is machine learning (ML). Many articles have focused on the use of ML for pattern recognition to detect and potentially diagnose various pathologies. However, AI algorithm development is now directed toward workflow management. AI can impact patient care at multiple stages of their imaging experience and assist in efficient and effective scheduling, imaging performance, worklist prioritization, image interpretation, and quality assurance. The purpose of this manuscript was to review the potential AI applications in radiology focusing on workflow management and discuss how ML will affect cardiothoracic imaging. Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.