deaths in numerous developing countries. On the whole, it is
regarded as the primary reason behind deaths in adults. The term
Heart disease encompasses the diverse diseases that affect the
heart. Heart disease was the major cause of casualties in the
different countries including India. Heart disease kills one person
every 34 seconds in the United States. Coronary heart disease,
Cardiomyopathy and Cardiovascular disease are some categories
of heart diseases. The term “cardiovascular disease” includes a
wide range of conditions that affect the heart and the blood vessels
and the manner in which blood is pumped and circulated through
the body. Cardiovascular disease (CVD) results in several illness,
disability, and death. The diagnosis of diseases is a vital and
intricate job in medicine.
Medical diagnosis is regarded as an important yet complicated
task that needs to be executed accurately and efficiently. The
automation of this system would be extremely advantageous.
Regrettably all doctors do not possess expertise in every sub
specialty and moreover there is a shortage of resource persons at
certain places. Therefore, an automatic medical diagnosis system
would probably be exceedingly beneficial by bringing all of them
together. Appropriate computer-based information and/or decision
support systems can aid in achieving clinical tests at a reduced
cost. Efficient and accurate implementation of automated system
needs a comparative study of various techniques available. This
paper aims to analyze the different predictive/ descriptive data
mining techniques proposed in recent years for the diagnosis of
heart disease.