Classification System for Heart Disease Using Bayesian Classifier

Magendram, Anusha (2007) Classification System for Heart Disease Using Bayesian Classifier. Masters thesis, Universiti Putra Malaysia.

[img] PDF
1341Kb

Abstract

Increase of hearth problem in this world is rising each day. Classification system for heart disease is a system that able to justify whether a patient has heart problem or not. This is a new approach that able to use by doctors to rectify the heart problem. This system was developing base on to three main part which is data processing, testing and implementation of the algorithm. In this system a Bayesian algorithm was used in order to implement the system. This system was mainly developing using java programming. Apache Tom cat was used as a server in order to run the application smoothly. This system is tested using the test and training data set. It has proven that the system able to provide an accurate result on justifying whether the patient has has problem or not. As a conclusion by using this system doctors able to improvise the effectiveness in medical field.

Item Type:Thesis (Masters)
Subject:Bayesian field theory
Subject:Heart - Diseases
Chairman Supervisor:Associate Professor Dr. Md. Nasir Sulaiman
Call Number:FSKTM 2007 9
Faculty or Institute:Faculty of Computer Science and Information Technology
ID Code:5886
Deposited By: Nur Izyan Mohd Zaki
Deposited On:05 May 2010 07:54
Last Modified:27 May 2013 07:25

Repository Staff Only: Edit item detail

Document Download Statistics

This item has been downloaded for since 05 May 2010 07:54.

View statistics for "Classification System for Heart Disease Using Bayesian Classifier"


Universiti Putra Malaysia Institutional Repository

Universiti Putra Malaysia Institutional Repository is an on-line digital archive that serves as a central collection and storage of scientific information and research at the Universiti Putra Malaysia.

Currently, the collections deposited in the IR consists of Master and PhD theses, Master and PhD Project Report, Journal Articles, Journal Bulletins, Conference Papers, UPM News, Newspaper Cuttings, Patents and Inaugural Lectures.

As the policy of the university does not permit users to view thesis in full text, access is only given to the first 24 pages only.