Clinical, Cultural, Computational, and Regulatory Considerations to Deploy AI in Radiology: Perspectives of RSNA and...

Marius George Linguraru¹, Spyridon Bakas¹, Mariam Aboian¹+11

• ¹From the Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, DC (M.G.L.); Divisions of Radiology and Pediatrics, George Washington University School of Medicine and Health Sciences, Washington, DC (M.G.L.); Division of Computational Pathology, Department of Pathology & Laboratory Medicine, School of Medicine, Indiana University, Indianapolis, Ind (S.B.); Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (M.A.); Department of Radiological Sciences, University of California Irvine, Irvine, Calif (P.D.C.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (A.E.F.); Department of Ophthalmology, University of Colorado Anschutz Medical Campus, Aurora, Colo (J.K.C.); Department of Applied Innovation and AI, Diagnósticos da América SA (DasaInova), São Paulo, Brazil (F.C.K.); Department of Diagnostic Imaging, Universidade Federal de São Paulo, São Paulo, Brazil (F.C.K.); Microsoft, Nuance, Burlington, Mass (M.P.L.); Department of Radiology and Biomedical Imaging and Center for Intelligent Imaging, University of California San Francisco, San Francisco, Calif (J.M.); Department of Radiology, The Ohio State University Wexner Medical Center, Columbus, Ohio (L.M.P.); Department of Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, Md (R.M.S.); Division of Diagnostic Imaging, University of Texas MD Anderson Cancer Center, Houston, Tex (C.C.W.); Medical Artificial Intelligence Laboratory, University of Lagos College of Medicine, Lagos, Nigeria (M.A.); and Department of Radiology, University of Pennsylvania, 3400 Spruce St, 1 Silverstein, Philadelphia, PA 19104-6243 (C.E.K.).