Title :
Automated diagnosis of coronary heart disease using neuro-fuzzy integrated system
Author :
Ansari, A.Q. ; Gupta, Neeraj Kumar
Author_Institution :
Dept. of Electr. Eng., Jamia Millia Islamia, New Delhi, India
Abstract :
Computational intelligence combines fuzzy systems, neural network and evolutionary computing. In this paper, Neuro-fuzzy integrated system for coronary heart disease is presented. In order to show the effectiveness of the proposed system, Simulation for automated diagnosis is performed by using the realistic causes of coronary heart disease. The results suggest that this kind of hybrid system is suitable for the identification of patients with high/low cardiac risk.
Keywords :
cardiology; diseases; fuzzy systems; medical diagnostic computing; neural nets; patient diagnosis; cardiac risk; computational intelligence; coronary heart disease automated diagnosis; evolutionary computing; neural network; neuro-fuzzy integrated system; patient identification; Arteries; Data processing; Diseases; Heart; Input variables; Mercury (metals); Training; Coronary Heart Disease; Neuro-Fuzzy Integrated system; Parameter Learning; Structure learning;
Conference_Titel :
Information and Communication Technologies (WICT), 2011 World Congress on
Conference_Location :
Mumbai
Print_ISBN :
978-1-4673-0127-5
DOI :
10.1109/WICT.2011.6141450
