EXTRACTION OF USEFUL INFORMATION OF A PATIENT USING DATA MINING TECHNIQUES
This paper discusses on the available literature on data mining in Medical applications.A categorization has been provided based on the data mining function implemented, and the preference criterion selected by the model.The usage of compressed ECG for fast and efficient Tele cardiology application is crucial, as ECG signals are enormously large in size.In this paper, we are demonstrating an innovative technique that performs real-time classification of CVD.Our proposed system initially uses data mining techniques, such as attribute selection (i.e., selects only a few features from the compressed ECG) and expectation maximization (EM) based clustering. These data mining techniques running on a hospital server generate a set of constraints for representing each of the abnormalities.Then, the patients mobile phone receives these set of constraints and employs a rule-based system that can identify each of abnormal beats in real time.
Cardiovascular diseases (CVD) Electrocardiogram (ECG) Expectation Maximization (EM) Naive Bayesian classifier
T.REVATHI DR.SUMATHI RAJESH
Dept. of Computer Science & Applications PSG College of Arts & Science Coimbatore-14 Tamil Nadu,Indi Department of Computer Science Chikkanna Govt. Arts College Tirupur -641602 Tamil Nadu,India
国际会议
成都
英文
1903-1907
2011-11-25（万方平台首次上网日期，不代表论文的发表时间）