Fostering a Healthy AI Ecosystem for Radiology: Conclusions of the 2018 RSNA Summit on AI in Radiology

Falgun H Chokshi; Adam E Flanders; Luciano M Prevedello; Curtis P Langlotz

doi:10.1148/ryai.2019190021

Fostering a Healthy AI Ecosystem for Radiology: Conclusions of the 2018 RSNA Summit on AI in Radiology

Radiol Artif Intell. 2019 Mar 27;1(2):190021. doi: 10.1148/ryai.2019190021. eCollection 2019 Mar.

Authors

Falgun H Chokshi¹, Adam E Flanders¹, Luciano M Prevedello¹, Curtis P Langlotz¹

Affiliation

¹ Departments of Radiology and Imaging Sciences and Biomedical Informatics, Emory University School of Medicine, 1364 Clifton Rd NE, Atlanta, GA 30322 (F.H.C.); Department of Radiology, Thomas Jefferson University Hospital, Philadelphia, Pa (A.E.F.); Department of Radiology, The Ohio State University Wexner Medical Center, Columbus, Ohio (L.M.P.); and Departments of Radiology and Biomedical Informatics, Stanford University School of Medicine, Stanford, Calif (C.P.L.).

Abstract

The 2018 RSNA Summit on AI in Radiology brought together a diverse group of stakeholders to identify and prioritize areas of need related to artificial intelligence in radiology. This article presents the proceedings of the summit with emphasis on RSNA's role in leading, organizing, and catalyzing change during this important time in radiology. © RSNA, 2019.

2019 by the Radiological Society of North America, Inc.