Abstract: Cardiac Disease (CD) is one of the major causes of death. An important task is to identify the Cardiac disease very minutely and precisely. Generally medical diagnostic errors are dangerous and costly. Worldwide they are leading to deaths. Data mining techniques are very important to minimize the diagnostic errors as well as to improve the patient’s safety. Data mining techniques are very effective in designing a medical support system and enrich ability to determine the unseen patterns and associations in clinical data. In this paper, the application of classification technique, decision tree for the detection of heart disease have been introduced. Classification tree uses many factors including age, blood sugar and blood pressure; it can detect the probability of patients fallen in CD by using fewer diagnostic tests which save time and money.

Abdul Aziz and Aziz Ur Rehman, “Detection of Cardiac Disease using Data Mining Classification Techniques” International Journal of Advanced Computer Science and Applications(IJACSA), 8(7), 2017. http://dx.doi.org/10.14569/IJACSA.2017.080734

@article{Aziz2017,
title = {Detection of Cardiac Disease using Data Mining Classification Techniques},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2017.080734},
url = {http://dx.doi.org/10.14569/IJACSA.2017.080734},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {7},
author = {Abdul Aziz and Aziz Ur Rehman}
}