Abstract:
Heart attack is a disease which has become the leading cause of death worldwide.
Particularly in the South Asian countries have a tremendous risk of heart attack at an early
age than any other ethnic group. Most often it’s challenging for medical practitioners to
predict heart attack as it requires experience and knowledge which is a complex task to
accomplish. This health industry has enormous amounts of data which is useful for making
effective conclusions using their hidden information. Using appropriate results and making
effective decisions on data, some superior data mining techniques are used such as Logistic
Regression, Decision Tree, K-NN. By using some properties like (age, gender, bp, stress
etc). we can be predicted the chances of heart attack. In this project, based on the global data
set. We applied data mining techniques to determine indicators responsible for the heart
attack. In the future, further incorporation & AI will help the systematic detectors.
