TY  - JOUR
T1  - Data Mining Association Rules for Heart Disease Prediction System
AU - Thanigaivel, R. AU - Kumar, K. Ramesh 
JO  - Research Journal of Applied Sciences
VL  - 10
IS  - 9
SP  - 469
EP  - 473
PY  - 2015
DA  - 2001/08/19
SN  - 1815-932x
DO  - rjasci.2015.469.473
UR  - https://makhillpublications.co/view-article.php?doi=rjasci.2015.469.473
KW  - Data mining
KW  -heart disease
KW  -prediction
KW  -web
KW  -diagnosis
AB  - Data mining techniques have been applied magnificently in many fields including business, science, the web, cheminformatics, bioinformatics and on different types of data such as textual, visual, spatial, real-time and sensor data. Medical data is still information rich but knowledge poor. There is a lack of effective analysis tools to discover the hidden relationships and trends in medical data obtained from clinical records. This study reviews the state of the art research on heart disease diagnosis and prediction.
ER  -