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The effect of scan and patient parameters on the diagnostic performance of AI for detecting coronary stenosis on coronary CT angiography

Rebecca Jonas, Emil Jernstedt Barkovich, Andrew Choi, William F. Griffin, Joanna Riess, Hugo P. Marques, Hyuk‐Jae Chang, Jung Hyun Choi, Joon‐Hyung Doh, Ae‐Young Her, Bon‐Kwon Koo, Chang‐Wook Nam, Hyung‐Bok Park, Sanghoon Shin, Jason Cole, Alessia Gimelli, Akram Khan, Bin Lü, Yang Gao, Faisal Nabi, Ryo Nakazato, U. Joseph Schoepf, Roel S. Driessen, Michiel J. Bom, Randall C. Thompson, James J. Jang, Michael Ridner, Chris Rowan, Erick Avelar, Philippe Généreux, Paul Knaapen, Guus A. de Waard, Gianluca Pontone, Daniele Andreini, Marco Guglielmo, Mouaz H. Al‐Mallah, Robert S. Jennings, Tami Crabtree, James P. Earls

2022Clinical Imaging17 citationsDOIOpen Access PDF

Topics & Concepts

MedicineStenosisRadiologyCoronary artery diseaseCoronary arteriesNuclear medicineArteryCardiologyCardiac Imaging and DiagnosticsCoronary Interventions and DiagnosticsAdvanced X-ray and CT Imaging
The effect of scan and patient parameters on the diagnostic performance of AI for detecting coronary stenosis on coronary CT angiography | Litcius