Title :
Heart disease predictor system based on Artificial Neural Network
Author :
Quijano, M. ; Tello, J.P. ; Cadena, Angela
Author_Institution :
Dept. de Ing. Electr. y Electron., Univ. del Norte, Barranquilla, Colombia
fDate :
April 29 2013-May 4 2013
Abstract :
An implementation of a system that classifies the health status of a subject with some success rate for Coronary Heart Disease presence is presented. The system is based on an Soft-Computing Technique (Artificial Neural Network) supported on some clinical parameters that allow to classify patient´s health between two categories: healthy or sick. A 94.2% of accuracy in a correct health status classification was acquired. This shows a tool that can assist medical personnel in Coronary Heart Disease diagnosis.
Keywords :
cardiology; classification; diseases; medical diagnostic computing; neural nets; patient diagnosis; Coronary Heart Disease diagnosis; Soft-Computing Technique; artificial neural network; health status classification; heart disease predictor system; medical personnel; patient health classification; Artificial neural networks; Conferences; Couplings; Diseases; Heart; RNA; Artificial Neural Networks; Classification; Coronary Heart Disease; MSE; predictor;
Conference_Titel :
Health Care Exchanges (PAHCE), 2013 Pan American
Conference_Location :
Medellin
Print_ISBN :
978-1-4673-6254-2
DOI :
10.1109/PAHCE.2013.6568350
