Association Rule Mining Method to Predict Coronary Artery Disease: KNHANES 2016–2018

Coronary artery disease (CAD) is a type of cardiovascular disease (CVD). According to a report from the World Health Organization (WHO) provided in 2017, it can be seen that CVD is the number one cause of death globally, and 85% of these deaths are estimated to be due to stroke and CAD. Then, the prevention of CAD is an essential public health topic in medical domain. In this paper, we aimed to find the risk factors of CAD for the prediction of CAD by using the association rule mining. In our experiment, we used the LASSO of feature selection approach. And we generated the rules based on the discovered risk factors. Then, we evaluated the discovered rules based on the confidence and support, and found helpful rules. We expect our results are useful for predicting the CAD more easily in real life.