English 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.
