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In the last decade, technical advances in the field of medical imaging significantly improved and broadened the application of coronary CT angiography (CCTA) for the non-invasive assessment of coronary artery disease. Recently, similar breakthroughs are happening in the post-processing, analysis and interpretation of radiological images. Technologies such as radiomics allow to extract significantly more information from scans than what human visual assessment is capable of. This allows the precision phenotyping of diseases based on medical images. The increased amount of information can then be analyzed using novel data analytic techniques such as machine learning (ML) and deep learning (DL), which utilize the power of big data to build predictive models, which seek to mimic human intelligence, artificially. Thanks to big data availability and increased computational power, these novel analytic …