ISSN : 2319-7323

INTERNATIONAL JOURNAL OF COMPUTER SCIENCE ENGINEERING

ABSTRACT

Title	:	Intelligent Predictive System Using Classification Techniques for Heart Disease Diagnosis
Authors	:	Basheer Mohamad Al-Maqaleh, Ahmed Mohamad Gasem Abdullah
Keywords	:	Data Mining; Diagnosis; Heart Disease; Decision Support System; Classification Techniques; Knowledge Discovery.
Issue Date	:	Jun 2017
Abstract	:	Heart disease continues to claim an alarming number of lives across the globe. The healthcare industry collects huge amounts of healthcare data, which are not mined to discover valuable information for efficient decision-making. The healthcare sector is still information rich but knowledge poo r. However, there is a lack of efficient analysis tools to discover hidden patterns and trends in medical dataset. In the healthcare industry, the data mining techniques are mainly used for classifying and predicting the diseases from medical datasets. In this paper, an intelligent predictive system using classification techniques for heart disease diagnosis, namely, J48 decision tree, Na�ve Bayes and Multi-Layer Perceptron Neural Network (MLPNN) are proposed. The main objective of this paper is to study these classification techniques to predict the heart disease and find the best technique of prediction. The obtained results are evaluated by the common performance metrics like Accuracy, TP-rate, Precision, F-Measure and ROC graph.
Page(s)	:	145-151
ISSN	:	2319-7323
Source	:	Vol. 6, No.6