A proficient methodology for the extraction of significant patterns
from the heart disease warehouses for heart attack prediction has
been presented in [7]. Initially, the data warehouse is preprocessed
in order to make it suitable for the mining process. Once
the preprocessing gets over, the heart disease warehouse is
clustered with the aid of the K-means clustering algorithm, which
will extract the data appropriate to heart attack from the
warehouse. Consequently the frequent patterns applicable to heart
disease are mined with the aid of the MAFIA algorithm from the
data extracted. In addition, the patterns vital to heart attack
prediction are selected on basis of the computed significant