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      Canadian Association of Radiologists White Paper on Artificial Intelligence in Radiology.

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          Abstract

          Artificial intelligence (AI) is rapidly moving from an experimental phase to an implementation phase in many fields, including medicine. The combination of improved availability of large datasets, increasing computing power, and advances in learning algorithms has created major performance breakthroughs in the development of AI applications. In the last 5 years, AI techniques known as deep learning have delivered rapidly improving performance in image recognition, caption generation, and speech recognition. Radiology, in particular, is a prime candidate for early adoption of these techniques. It is anticipated that the implementation of AI in radiology over the next decade will significantly improve the quality, value, and depth of radiology's contribution to patient care and population health, and will revolutionize radiologists' workflows. The Canadian Association of Radiologists (CAR) is the national voice of radiology committed to promoting the highest standards in patient-centered imaging, lifelong learning, and research. The CAR has created an AI working group with the mandate to discuss and deliberate on practice, policy, and patient care issues related to the introduction and implementation of AI in imaging. This white paper provides recommendations for the CAR derived from deliberations between members of the AI working group. This white paper on AI in radiology will inform CAR members and policymakers on key terminology, educational needs of members, research and development, partnerships, potential clinical applications, implementation, structure and governance, role of radiologists, and potential impact of AI on radiology in Canada.

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          Author and article information

          Journal
          Can Assoc Radiol J
          Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
          Elsevier BV
          1488-2361
          0846-5371
          May 2018
          : 69
          : 2
          Affiliations
          [1 ] Department of Radiology, Université de Montréal, Montréal, Québec, Canada; Centre de recherche du Centre hospitalier de l'Université de Montréal, Montréal, Québec, Canada. Electronic address: an.tang@umontreal.ca.
          [2 ] Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada; School of Biomedical Engineering, University of British Columbia, Vancouver, British Columbia, Canada.
          [3 ] Department of Medical Imaging, CISSS Lanaudière, Université Laval, Joliette, Québec, Canada.
          [4 ] Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada.
          [5 ] Department of Radiology, McGill University Health Center, Montréal, Québec, Canada.
          [6 ] Department of Medical Imaging, St. Michael's Hospital, University of Toronto, Toronto, Ontario, Canada.
          [7 ] Department of Radiology, University of Ottawa, Ottawa, Ontario, Canada.
          [8 ] Department of Radiology, British Columbia's Children's Hospital, University of British Columbia, Vancouver, British Columbia, Canada.
          [9 ] Department of Research, Mayo Clinic, Phoenix, Arizona, USA.
          [10 ] Department of Radiology, Université de Sherbrooke, Sherbrooke, Québec, Canada.
          [11 ] Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton, Alberta, Canada.
          [12 ] Department of Radiology, National Jewish Health, Denver, Colorado, USA.
          Article
          S0846-5371(18)30030-5
          10.1016/j.carj.2018.02.002
          29655580

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