Title :
Myocardial infarction diagnosis by a neural network
Author :
Cházaro, A. ; Cravens, G. ; Eberhart, R.
Author_Institution :
Electr. Eng. Dept., Purdue Sch. of Eng. & Technol., Indianapolis, IN, USA
fDate :
29 Oct-1 Nov 1998
Abstract :
A system was developed to diagnose myocardial infarction using a backpropagation neural network. A data set of 563 patients was used. Performance was similar to that obtained by emergency room physicians
Keywords :
backpropagation; cardiology; medical diagnostic computing; medical expert systems; neural nets; backpropagation neural network; data preprocessing; decision hypersurface; error threshold; missing values handling; myocardial infarction diagnosis; training set; Backpropagation algorithms; Biomedical engineering; Education; Erbium; History; Logistics; Medical diagnostic imaging; Myocardium; Neural networks; Pain;
Conference_Titel :
Engineering in Medicine and Biology Society, 1998. Proceedings of the 20th Annual International Conference of the IEEE
Conference_Location :
Hong Kong
Print_ISBN :
0-7803-5164-9
DOI :
10.1109/IEMBS.1998.747068
