Abstract: A method of establishing a coronary artery disease (CAD) prediction model for CAD screening includes establishing a data set in a computer equipment; entering the data set and corresponding future CAD condition of asymptomatic individuals into a machine learning component; selecting a plurality of robust variables from the clinical data and the cardiovascular markers of the cardiovascular markers panel by using feature selection methods; establishing the CAD prediction model by using machine learning methods; uploading new clinical data and new results of the cardiovascular markers to the cloud-based platform when any asymptomatic individuals undergo the health examination, and performing calculation and analysis by the CAD prediction model; and notifying the asymptomatic individuals of having a high risk of encountering a CAD event or not in a certain period of follow-up time.

Abstract: A coronary artery disease (CAD) screening method includes 1) collecting clinical information of asymptomatic individuals and testing a plurality of samples of the individuals by using a cardiovascular markers panel including a plurality of cardiovascular markers; 2) entering the clinical information and the test results and the corresponding CAD states of the individuals into a machine learning platform; 3) selecting a plurality of roust variables from the clinical information and the cardiovascular markers of the cardiovascular markers panel by using feature selection methods; 4) using a machine learning algorithm embedded in the machine learning platform to establish a CAD prediction model; and 5) entering clinical information and sample data obtained by using the cardiovascular markers panel for an individual being screened into the CAD prediction model for calculation and analysis, thereby determining whether the individual being screened has CAD or not.