Imaging AI in Practice: A Demonstration of Future Workflow Using Integration Standards

Walter F Wiggins1, Kirti Magudia1, Teri M Sippel Schmidt1

  • 1Department of Radiology, Duke University School of Medicine, DUMC Box 3808, 2301 Erwin Rd, Durham, NC 27710 (W.F.W.); Department of Radiology & Biomedical Imaging, University of California, San Francisco, Calif (K.M., M.D.K.); Department of Biomedical Engineering, Marquette University, Milwaukee, Wis (T.M.S.S.); Departments of Biomedical Engineering (T.M.S.S.) and Radiology (S.D.O.), Medical College of Wisconsin, Milwaukee, Wis; Department of Informatics, Radiological Society of North America, Oak Brook, Ill (C.D.C.); Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (K.P.A.); and Mass General Brigham Center for Clinical Data Science, Boston, Mass (K.P.A.).

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