| dc.description.abstract | Heart disease is the second of leading cause of death in Taiwan affect people′s health. Except for taking medicine and Percutaneous Transluminal Coronary Angioplasty (PTCA), cardiac surgery is an effective way to treat heart disease. There are three different types of surgeries which are coronary artery bypass graft surgery (CABG), heart valve surgery (VALVE) and aortic surgery (AO) here. Different surgery contains different factors, using the factors in each surgery to do data mining, the factors including patient’s basic information, such as: birthday, height, weight, gender…etc. Besides patient’s basic information, patient’s data before, during and after surgery are included, for example: blood pressure, the brand and frequency of drugs, number of surgeries, if patients with heart failure or complications or not...etc. Mining this data can analyze the different of patient’s status between before and after surgery, whether different brand of drug will influent patient or not, and using what things will affect patient’s survival...etc. After analysis of these data, doctor can estimate patients’ possible changes after surgery by postoperative medication and states before and during surgery. Not only can predict preoperative and postoperative differences, but also can estimate patients’ survival rate by their condition, such as: if the patient need secondary surgery or get complications after surgery or not. In addition to let doctors understand patients’ conditions conveniently, even are able to reduce the mortality rate of patients and error of surgery. It is good for the future of cardiac surgery and can make the surgical patients and patients′ families increase confidence of surgery. | en_US |