Decision Support System for Heart Disease Diagnosis Using Neural Network

Abstract

Purpose: The objective of this paper is to experiment Decision Support System for Heart Disease Diagnosis Using Neural Network Design/Methodology/Approach: A set of experiments was performed on a sample database of 78 patients' records, 13 input variables (Age, Blood Pressure, Angiography's report etc.) are used for training and testing of the Neural Network. Findings: We therefore conclude that ANN is a fast alternative to classical statistical techniques for prediction and modelling of experimental data. It is believed that neural networks will have extensive application to biomedical problems in the next few years. Research Limitations: This paper was limited to specific patients only. Managerial Implications: Error made by human being can be avoided in this system; hence the system is more reliable and helps the doctor to take correct decision. Originality/Value: The paper provides the original work of authors in the fields of decision support system