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Purpose: Recent guidelines provide broader support for the use of less invasive imaging modalities for the evaluation of patients with stable chest pain. Coronary CT angiography (CCTA) uses increasingly sophisticated techniques to improve evaluation of coronary lesions. The purpose of this study is to describe one center's experience implementing AI-assisted advanced imaging techniques to diagnose coronary artery disease. Materials & methods: Retrospective study of patients who had AI-assisted CCTA interpretation, including a subgroup who underwent fractional flow reserve CT (FFR-CT) and invasive coronary angiography. Descriptive statistics summarized baseline characteristics and univariate statistics compared findings between groups of patients with and without anatomically and hemodynamically significant lesions based on FFR-CT. For patients who underwent invasive coronary angiography, concordance between CCTA and angiography was evaluated. Results: Of 532 included patients, AI-assisted CCTA identified statistically significant difference in calcification scores, plaque types and total plaque volume between lesions