Data mining has become a fundamental methodology for
computing applications in medical informatics. Progress in
data mining applications and its implications are manifested in
the areas of information management in healthcare
organizations, health informatics, epidemiology, patient care
and monitoring systems, assistive technology, large-scale
image analysis to information extraction and automatic
identification of unknown classes. Various algorithms
associated with data mining have significantly helped to
understand medical data more clearly, by distinguishing
pathological data from normal data, for supporting decisionmaking
as well as visualization and identification of hidden
complex relationships between diagnostic features of different
patient groups.
Coronary Heart Disease (CHD) is a major cause of disability
in adults in and common cause of death in Europe, USA,
South Asia, etc., It has been predicted that all the regions of
the world will be affected due to CHD by the year 2020 [1].
Coronary Heart Disease refers to the failure of coronary
circulation to supply adequate circulation to cardiac muscle
and its surrounding tissue. This restricts the supply of blood
and oxygen to the heart, particularly during exertion when the
myocardial metabolic demands are increased. As the degree
of coronary artery disease progresses, there may be nearcomplete
obstruction of the lumen of the coronary artery,
severely restricting the flow of oxygen-carrying blood to the myocardium. Individuals with this degree of coronary artery
disease typically have suffered from one or more myocardial
infarctions (heart attacks), and may have signs and symptoms
of chronic coronary ischemia, including symptoms of angina
at rest and flash pulmonary edema [2].