| 英文摘要 |
Heart disease has been the second leading cause of death over the last five years in Taiwan. Many sudden cardiac deaths were attributed to coronary artery disease (CAD). CAD is a chronic process with a long asymptomatic latent period, which provides a chance for early preventive interventions. Since the incidence of CAD is largely explained by modifiable lifestyle-related risk factors, a logical way for preventing CAD is to increase awareness and encourage people developing CAD to reduce risks through health-promoting diet and lifestyle. In this study, a website was developed to provide a series of functions for the users to realize their CAD risks. The functions include risk computation, risk tracking and risk alerting. The risk computation is based on an instance-based learning algorithm. The set of training instances contains information about demographics and multiple plasma biomarkers. The biomarkers include traditional and nontraditional risk factors of CAD. The tracking function of the website helps the user be aware of his/her CAD risk trend. The risk alerting function help the user notice how his/her health is different from those of the CAD patients/non-CAD individuals in the training instances in terms of CAD risk factors. |