Canadian Association of Radiologists White Paper on Artificial Intelligence in Radiology

Canadian Association of Radiologists (CAR) Artificial Intelligence Working Group

Research output: Contribution to journalReview article

79 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)120-135
Number of pages16
JournalCanadian Association of Radiologists Journal
Volume69
Issue number2
DOIs
StatePublished - May 2018

Keywords

  • Artificial intelligence
  • Deep learning
  • Healthcare
  • Imaging
  • Machine learning
  • Medicine
  • Quality improvement
  • Radiology

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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