Assessing Radiology Research on Artificial Intelligence: A Brief Guide for Authors, Reviewers, and Readers-From the Editorial Board.

David A Bluemke Linda Moy Miriam A Bredella Birgit B Ertl-Wagner Kathryn J Fowler Vicky J Goh Elkan F Halpern Christopher P Hess Mark L Schiebler Clifford R Weiss

Radiology

From the Department of Radiology, University of Wisconsin Madison School of Medicine and Public Health, 600 Highland Dr, Madison, WI 53792 (D.A.B., M.L.S.); Department of Radiology, New York University, New York, NY (L.M.); Department of Musculoskeletal Radiology (M.A.B.) and Institute for Technology Assessment (E.F.H.), Massachusetts General Hospital, Boston, Mass; Department of Medical Imaging, Hospital for Sick Children, University of Toronto, Toronto, Canada (B.B.E.W.); Department of Radiology, University of California-San Diego, San Diego, Calif (K.J.F.); Department of Cancer Imaging, Division of Imaging Sciences & Biomedical Engineering, Kings College London, London, England (V.J.G.); Department of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, Calif (C.P.H.); and Department of Radiology and Radiologic Science, The Johns Hopkins University School of Medicine, Baltimore, Md (C.R.W.).

Published: March 2020

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http://dx.doi.org/10.1148/radiol.2019192515	DOI Listing

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