An Ill-identified Classification to Predict Cardiac Disease Using Data Clustering

The health care industry contains large amount of health care data with hidden information. This information is useful for making effective decision. For getting appropriate result from the hidden information computer based data mining techniques are used. Previously Neural Network NN is widely used for predicting cardiac disease. In this paper, a Cardiac Disease Prediction System CDPS is developed by using data clustering. The CDPS system uses 15 parameters to predict the disease, for example BP, Obesity, cholesterol, etc. This 15 attributes like sex, age, weight are given as the input. In this paper by using the patient’s medical record, an illdefined classification is used at the early stage of the patient to diagnose the cardiac disease. Based on the result the patients are advised to keep the sensor to predict them.