Research Area: Machine Learning
Heart disease is a most harmful one that will cause death. It has a serious long term disability. This disease attacks a person so instantly. Medical data is still information rich but knowledge poor. Therefore diagnosing patients correctly on the basis of time is an exigent function for medical support. An invalid diagnosis done by the hospital leads for losing reputation. The precise diagnosis of heart disease is the dominant biomedical issue. The motivation of this paper is to develop an efficacious treatment using data mining techniques that can help remedial situations. Further data mining classification algorithms like decision trees, neural networks, Bayesian classifiers, Support vector machines, Association Rule, K- nearest neighbour classification are used to diagnosis the heart diseases. Among these algorithms Support Vector Machine (SVM) gives best result.
Keywords:
Heart Disease
Data Mining Techniques
Machine Learning
Deep Learning
Author(s) Name: Cincy Raju; E Philipsy; Siji Chacko; L Padma Suresh; S Deepa Rajan
Journal name:
Conferrence name: Conference on Emerging Devices and Smart Systems (ICEDSS)
Publisher name: IEEE
DOI: 10.1109/ICEDSS.2018.8544333
Volume Information:
