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Can AI Capture and Quantify Clinical Expertise? Implications for Intracoronary Imaging in Percutaneous Coronary Intervention

Can AI Capture and Quantify Clinical Expertise? Implications for Intracoronary Imaging in Percutaneous Coronary Intervention

Ricardo Petraco ^1,2, Rahul Bahl ³, Guilherme Almeida ^2,4, Daniel Bandeira ⁵, Henry Seligman ³, Anissa Alloula ⁶, Abigail Demuyakor ⁵, Alexandra J Lansky ⁵, Tom Johnson ⁷, Darrel Francis ^2,3, Gary S Mintz ⁸, Matthew Shun-Shin ^2,3, Daniel Chamié ^2,5

Ricardo Petraco ^1,2, Rahul Bahl ³, Guilherme Almeida ^2,4

¹Department of Cardiology, Imperial College Healthcare NHS Trust, London, United Kingdom.
²London Core Laboratory, London, United Kingdom.
³National Heart and Lung Institute, Imperial College London, London, United Kingdom.
⁴Department of Medicine, Federal Institute of Sergipe, Sergipe, Brazil.
⁵Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut.
⁶Big Data Institute, University of Oxford, Oxford, United Kingdom.
⁷Bristol Heart Institute, University of Bristol, Bristol, United Kingdom.
⁸Cardiovascular Research Foundation, New York, New York.

⁰Department of Cardiology, Imperial College Healthcare NHS Trust, London, United Kingdom.

Journal of the Society for Cardiovascular Angiography & Interventions +

|

April 15, 2025

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Summary

No abstract available on PubMed

Keywords:

artificial intelligence coronary artery disease intravascular imaging intravascular ultrasound optical coherence tomography

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