Human heart disease prediction system using data mining techniques

Title

Human heart disease prediction system using data mining techniques

Creator

Thomas J.; Princy R.T.

Description

Nowadays, health disease are increasing day by day due to life style, hereditary. Especially, heart disease has become more common these days, i.e. life of people is at risk. Each individual has different values for Blood pressure, cholesterol and pulse rate. But according to medically proven results the normal values of Blood pressure is 120/90, cholesterol is and pulse rate is 72. This paper gives the survey about different classification techniques used for predicting the risk level of each person based on age, gender, Blood pressure, cholesterol, pulse rate. The patient risk level is classified using datamining classification techniques such as Nae Bayes, KNN, Decision Tree Algorithm, Neural Network. etc., Accuracy of the risk level is high when using more number of attributes. 2016 IEEE.

Source

Proceedings of IEEE International Conference on Circuit, Power and Computing Technologies, ICCPCT 2016

Date

2016-01-01

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

classification Techniques; Decision Tree Algorithm; heart disease; KNN; Nae Bayes; Neural Network; Risk level

Coverage

Thomas J., Department of Computer Science and Engineering, Christ University, Faculty of Engineering, Bangalore, 560060, India; Princy R.T., Department of Information Technology, Christ University, Faculty of Engineering, Bangalore, 560060, India

Rights

Restricted Access

Relation

ISBN: 978-150901277-0

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/ICCPCT.2016.7530265

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