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CIRSE Position Paper on Artificial Intelligence in Interventional Radiology.

Arash Najafi1, Roberto Luigi Cazzato2, Bernhard C Meyer3

  • 1Department of Radiology and Nuclear Medicine, Institut für Radiologie und Nuklearmedizin, Kantonsspital Winterthur, Brauerstrasse 15, 8401, Winterthur, Switzerland. najafi.arash@gmail.com.

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Artificial intelligence (AI) will significantly impact healthcare, particularly in interventional radiology (IR). IR professionals must lead the integration of AI to optimize patient care and resources.

Keywords:
AIArtificial intelligenceIRInterventional radiologyMLMachine learning

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Area of Science:

  • Medical Imaging
  • Artificial Intelligence in Medicine

Background:

  • Artificial intelligence (AI) is rapidly advancing, with significant implications for healthcare delivery and resource optimization.
  • Interventional Radiology (IR), a technology-reliant specialty, is uniquely positioned to leverage AI advancements.

Discussion:

  • AI's integration into clinical medicine promises improved patient care and operational efficiency.
  • Interventional radiologists must actively participate in the development, training, and implementation of AI systems.
  • Understanding and leading AI adoption is crucial for the future of IR.

Key Insights:

  • AI offers transformative potential for various medical fields, including IR.
  • Proactive engagement by interventional radiologists is essential for successful AI implementation.
  • The specialty must embrace AI to drive innovation and enhance clinical practice.

Outlook:

  • AI is expected to reshape interventional radiology, necessitating a forward-thinking approach.
  • Collaboration between clinicians and AI developers will be key to realizing AI's full potential in IR.
  • The future of IR involves embracing AI as a tool for enhanced diagnostics and treatments.