BackgroundThe interpretation of coronary computed tomography angiography (CCTA) stenosis may be difficult among radiologists of different experience levels. Artificial intelligence (AI) may improve the diagnostic performance.PurposeTo investigate whether the diagnostic performance and time efficiency of radiologists with different levels of experience in interpreting CCTA images could be improved by using CCTA with AI assistance (CCTA-AI).Material and MethodsThis analysis included 200 patients with complete CCTA and invasive coronary angiography (ICA) data, using ICA results as the...