TY - JOUR
AU - Weiss, Clifford                            R.
AB - COMMUNICATIONS • FROM THE EDITOR Assessing Radiology Research on Artificial Intelligence: A Brief Guide for Authors, Reviewers, and Readers—From the Radiology Editorial Board David A. Bluemke, MD, PhD • Linda Moy, MD • Miriam A. Bredella, MD • Birgit B. Ertl-Wagner, MD, MHBA • Kathryn J. Fowler, MD • Vicky J. Goh, MBBCh • Elkan F. Halpern, PhD • Christopher P. Hess, MD • Mark L. Schiebler, MD • Clifford R. Weiss, MD 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.); Depart- ment 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.). Received November 12, 
TI - Assessing Radiology Research on Artificial Intelligence: A Brief                    Guide for Authors, Reviewers, and Readers—From the                        Radiology Editorial Board
JF - Radiology
DO - 10.1148/radiol.2019192515
DA - 2020-03-31
UR - https://www.deepdyve.com/lp/radiological-society-of-north-america-inc/assessing-radiology-research-on-artificial-intelligence-a-brief-guide-E2AqeqYuVI
SP - 487
EP - 489
VL - 294
IS - 3
DP - DeepDyve
ER -