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An Introductory Guide to Artificial Intelligence in Interventional Radiology: Part 1 Foundational Knowledge.

Blair Edward WarrenAlexander BilbilyJudy Wawira GichoyaAaron ConwayBen LiAly FawzyCamilo BarragánArash JaberiSebastian Mafeld
Published in: Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes (2024)
Artificial intelligence (AI) is rapidly evolving and has transformative potential for interventional radiology (IR) clinical practice. However, formal training in AI may be limited for many clinicians and therefore presents a challenge for initial implementation and trust in AI. An understanding of the foundational concepts in AI may help familiarize the interventional radiologist with the field of AI, thus facilitating understanding and participation in the development and deployment of AI. A pragmatic classification system of AI based on the complexity of the model may guide clinicians in the assessment of AI. Finally, the current state of AI in IR and the patterns of implementation are explored (pre-procedural, intra-procedural, and post-procedural).
Keyphrases
  • artificial intelligence
  • machine learning
  • big data
  • deep learning
  • healthcare
  • primary care
  • clinical practice
  • palliative care
  • randomized controlled trial
  • quality improvement