Call For Paper Volume:4 Issue:10 Oct'2017 |


Publication Date : 10/05/2015

Author(s) :

Dr. G. Rasitha Banu MCA., M.Phil., Ph.D., , J.H.BOUSAL JAMALA MCA.,.

Volume/Issue :
Volume 2
Issue 5
(05 - 2015)

Abstract :

Data mining techniques are used to analyze this rich collection of data from different perspectives and deriving useful information. This project intends to design and develop diagnosis and prediction system for heart diseases based on predictive mining. Heart disease is a term that assigns to a large number of medical conditions related to heart. These medical conditions describe the abnormal health conditions that directly influence the heart and all its parts. Heart disease is a major health problem in to days time. This paper aims at analyzing the various data mining techniques introduced in recent years for heart disease prediction. Cardiovascular disease remains the biggest cause of deaths worldwide. This paper, a new unsupervised classification system is adopted for heart attack prediction at the early stage using the patient’s medical record. The information in the patient record are preprocessed initially using data mining techniques and then the attributes are classified using a Fuzzy C means classifier. In the classification stage 13 attributes are given as input to the Fuzzy C Means (FCM) classifier to determine the risk of heart attack. FCM is an unsupervised clustering algorithm, which allows one piece of data to belong to two or more clusters

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May 9, 2015