Preliminary Study On The Cardiac Configurations Of The Hypertension Based On Data Mining Technology

Objective:To study the basic clinical information and left ventricularconfigurations of hypertensive patients using data mining technologies,Dig outthe potential、 value informations between the impact of factors and cardiacconfiguration. To analyze the trend of the various indicators and the dynamic changes ofthe heart configuration.Methods:650hypertensive patients were detected by RT-3DE and conventionalechocardiography from2012.1to2013.2. Firstly, we measured the height, weight andBSA of subjects;Secondly, analyzed the cardiac configuration parameters(includingLAD,LAV,LVEDD, IVSD, LVPWD,, LVM);Thirdly, studied the standardized left heartconfiguration parameters (including LADI,LAVI, LVEDDI, VSDI, LVPWDI,LVMI),and to check the basic information of the patients (patients with or withouthypertension genetic history, the level of blood glucose、blood lipids、blood pressure,whether high-salt diet, whether low-protein diet, and ECG changes, etc.)This as a datasource to create the database，the database management tool is SQL Server2008， thedata mining tools is SQLServer2008_DMAddin and office2007, To study the basicclinical information and left ventricular configurations of hypertensive patients,Dig outthe potential and value informations between the impact of factors and cardiacconfiguration. To analyze the trend of the various indicators and the dynamic changes ofthe heart configuration. To establish the aided diagnosis system of the hypertensionabout the left cardiac heart configuration.Result: To establish the relational database of hypertensive patients about the clinical information and the cardiac configuration, And to convert the relationaldatabase to the transaction databases,Provided a way to analyze the left ventricularconfiguration factors and some associated measurement indicators about thehypertension patients,We can know the cardiac configuration closely related to genetichistory, high blood pressure levels, left atrial volume by the association rule mining,The aided diagnosis system was design preliminary by extracting association rules.Conclusion: Data mining technology can makes full use of the large amount ofmedical information, which can timely and accurately predict the cardiac configurationby extracting valuable diagnostic rules, and has a certain practical significance ofclinical aided diagnosis.