Thus, we designed a case-control study to explore new, common and well-defined facial characteristics associated with CAD and evaluate the diagnostic efficacy of appearence factors in CAD. We will recuit 100 patients with triple-vessel or left main diseases (3VD/LM group) and 400 patients without coronary lesion stenosis≥ 50% (No CAD group) judged by coronary computer tomography or coronary angiography. We will collect patients' baseline information and facial images. One hand, we will explore the facial factors associated with CAD by comparing the exposure rates of different facial factors in 3VD/LM group and No CAD group based on artificial intelligence technology. On the other hand, we will build a new CAD risk model by combining Framingham risk score and facial factors associated with CAD, and compare the diagnostic efficacy of the new model with Framingham risk score.