Bending the Artificial Intelligence Curve for Radiology: Informatics Tools From ACR and RSNA.

Artificial intelligence (AI) will reshape radiology over the coming years. The radiology community has a strong history of embracing new technology for positive change, and AI is no exception. As with any new technology, rapid, successful implementation faces several challenges that will require creation and adoption of new integration technology. Use cases important to real-world application of AI are described, including clinical registries, AI research, AI product validation, and computer assistance for radiology reporting. Furthermore, the informatics technologies required for successful implementation of the use cases are described, including open Computer-Assisted Radiologist Decision Support, ACR Assist, ACR Data Science Institute use cases, common data elements (, RadLex (, LOINC/RSNA RadLex Playbook (, and Radiology Report Templates (

Journal of the American College of Radiology : JACR. 2019 Oct;16(10):1464-1470.

ISSN 1558-349X

Authors: Marc Kohli, Tarik Alkasab, Ken Wang, Marta E Heilbrun, Adam E Flanders, Keith Dreyer, Charles E Kahn

Copyright © 2019 American College of Radiology. All rights reserved.

PMID 31319078

PubMed BibTeX