• Bernardo C Bizzo, Renata R Almeida, Mark H Michalski, and Tarik K Alkasab.
• Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts; MGH & BWH Center for Clinical Data Science, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts.
• J Am Coll Radiol. 2019 Sep 1; 16 (9 Pt B): 1351-1356.

AbstractRecent advances in artificial intelligence (AI) are providing an opportunity to enhance existing clinical decision support (CDS) tools to improve patient safety and drive value-based imaging. We discuss the advantages and potential applications that may be realized with the synergy between AI and CDS systems. From the perspective of both radiologist and ordering provider, CDS could be significantly empowered using AI. CDS enhanced by AI could reduce friction in radiology workflows and can aid AI developers to identify relevant imaging features their tools should be seeking to extract from images. Furthermore, these systems can generate structured data to be used as input to develop machine learning algorithms, which can drive downstream care pathways. For referring providers, an AI-enabled CDS solution could enable an evolution from existing imaging-centric CDS toward decision support that takes into account a holistic patient perspective. More intelligent CDS could suggest imaging examinations in highly complex clinical scenarios, assist on the identification of appropriate imaging opportunities at the health system level, suggest appropriate individualized screening, or aid health care providers to ensure continuity of care. AI has the potential to enable the next generation of CDS, improving patient care and enhancing providers' and radiologists' experience.Copyright © 2019 American College of Radiology. Published by Elsevier Inc. All rights reserved.

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