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Continuous Learning AI in Radiology: Implementation Principles and Early Applications

Oleg S Pianykh1, Georg Langs1, Marc Dewey1

  • 1From the Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit St, FND-210, Boston, MA 02114-2698 (O.S.P., J.A.B.); International Society for Strategic Studies in Radiology (IS3R), Vienna, Austria (M.D., D.R.E., C.J.H., S.O.S., J.A.B.); Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria (G.L., C.J.H.); Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Boston, Mass (G.L.); Department of Radiology, Charité-Universitätsmedizin, Berlin, Germany (M.D.); Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Calif (D.R.E.); and Institute of Clinical Radiology and Nuclear Medicine, University Medical Center Mannheim, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany (S.O.S.).

Radiology
|August 26, 2020
PubMed

Keywords:
machine learningmedical imagingclinical decision supportpredictive analytics

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