Affiliations: [a] Glorious Sun School of Business and Management, Donghua University, Shanghai, China
| [b] School of Computer Science and Technology, Donghua University, Shanghai, China
| [c] RuiJin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
Correspondence:
[*]
Corresponding author. Yan Zhao, Glorious Sun School of Business and Management, Donghua University, Shanghai, China. E-mail: zy@rjh.com.cn.
Abstract: Hypertension is a common disease. The treatment of hypertension is one of the major public health problems in the world. Currently, in the clinical treatment of hypertension, most of which are with oral medicine in order to control the blood pressure. However, because every patient differs in pathogeny and symptom of hypertension, and the combination of various medicines is also complex. All these factors make it difficult for clinicians to give the best drug treatment for each patient. Thus, this paper takes advantage of the data mining technology to analyze the medication treatment schemes of hypertension and find out the key factors that affect the success of each treatment scheme. These key factors will be regarded as criteria to guide clinicians to prescribe medications for patients so as to reduce the pain of patient, improve medical quality and save limited health resources.
Keywords: Big data, data mining, hypertension, drug factors
