Abstract
Coronary artery calcium (CAC) scoring improves traditional risk factor-based coronary heart disease (CHD) risk stratification. Here, the contribution of CAC scoring to a traditional 10-year CHD risk prediction scores and new artificial intelligence methods used to automate CAC scoring were reviewed. Research shows that traditional risk factors tend to overestimate or underestimate the actual risk of CHD, meaning that including CAC score in the risk stratification has potential to reduce over- and undertreatment. The automated CAC scoring methods are shown to be accurate and significantly more time-effective than the commonly used semi-automated method.