Heart Disease Diagnosis using KNN Clustering Technique |
Author(s): |
Babitha M , Adhiyamaan college of Engineering,Hosur; Manikandan M, Adhiyamaan college of Engineering,Hosur |
Keywords: |
KNN, Clustering Technique, ICD |
Abstract |
Data mining is an iterative progress in which evolution is defined by detection, through usual or manual methods. Knowledge discovery and data mining have found various applications in scientific domain. Heart disease is a term for defining a huge amount of healthcare conditions that are related to the heart. This medicinal condition defines the unpredicted health conditions that directly control all the parts of the heart. Different data mining techniques such as association rule mining, classification, clustering are used to predict the heart disease in health care industry. The heart disease database is pre-processed to make the mining process more efficient. The pre-processed data is clustered using clustering algorithms like K-Nearest Neighbour (KNN) to cluster relevant data in database. International Classification of Diseases (ICD) Data is used for mining maximal frequent patterns in heart disease database. The frequent patterns can be classified using KNN algorithm as training algorithm using the concept of information entropy. The results showed that the designed prediction system is capable of predicting the heart attack with good accuracy. |
Other Details |
Paper ID: IJSRDV5I10414 Published in: Volume : 5, Issue : 1 Publication Date: 01/04/2017 Page(s): 474-476 |
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