J Am Coll Radiol. 2019 Oct;16(10):1464-1470. doi: 10.1016/j.jacr.2019.06.009. Epub 2019 Jul 15.
Kohli M, Alkasab T, Wang K, Heilbrun ME, Flanders AE, Dreyer K, Kahn CE Jr.
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 (radelement.org), RadLex (radlex.org), LOINC/RSNA RadLex Playbook (loinc.org), and Radiology Report Templates (radreport.org).
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