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Introduction: Computed Tomography (CT) is a widely used imaging modality for the detection of coronary
artery disease. However, the accuracy of CT is dependent on operator skill, image
quality and reader experience. This study aimed to assess the utility of a novel machine
learning (ML) technique to detect cardiac substructures in CT.
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