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Artificial Intelligence in Imaging: The Radiologist's Role.

Daniel L Rubin1

  • 1Department of Biomedical Data Science, Radiology, and Medicine (Biomedical Informatics Research), Stanford University, Stanford, California.

Journal of the American College of Radiology : JACR
|September 8, 2019
PubMed
Summary
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Radiologists must actively engage with artificial intelligence (AI) in medical imaging. This involves evaluating clinical needs, assessing AI tools formally, and maintaining expertise to avoid overreliance on technology.

Area of Science:

  • Medical Imaging
  • Artificial Intelligence
  • Radiology

Background:

  • Rapid advancements in artificial intelligence (AI) have led to a surge in decision support tools.
  • AI development is primarily driven by non-radiologists, with limited radiologist participation.
  • Radiologists' involvement is often confined to education, lacking guidance on tool selection and value quantification.

Purpose of the Study:

  • To outline the crucial role of radiologists in the adoption and integration of AI in medical imaging.
  • To propose actionable strategies for radiologists to actively participate in AI development and deployment.
  • To emphasize the importance of critical evaluation and expertise maintenance for radiologists using AI tools.

Main Methods:

  • Analysis of current AI trends in medical imaging.
Keywords:
Artificial intelligenceevaluationimagingradiology

Related Experiment Videos

  • Identification of gaps in radiologist engagement with AI.
  • Development of a framework for radiologist involvement in AI adoption.

    • Main Results:

    • Radiologists are underrepresented in AI development and decision-making processes.
    • There is a need for structured approaches to evaluate AI tools for clinical practice.
    • Radiologists require guidance on selecting and quantifying the value of AI solutions.

    Conclusions:

    • Radiologists must take a proactive role in the AI revolution in medical imaging.
    • Key engagement strategies include assessing clinical needs, formal evaluation of AI tools, and continuous professional development.
    • Maintaining expertise and critically evaluating AI are essential to ensure patient safety and optimal outcomes.