A new approach to medical diagnosis

Author

Schizas, C.N. ; Pattichis, C.S. ; Middleton, L.T.

Author_Institution

Dept. of Comput Sci., Cyprus Univ., Nicosia, Cyprus

fYear

1992

fDate

18-20 Aug 1992

Firstpage

207

Lastpage

212

Abstract

The diagnostic usefulness of artificial neural networks (ANNs) is explored by means of an integrated system for medical diagnosis. The models were developed by using the unsupervized self organizing feature maps algorithm. Clinical and laboratory data for training and testing the ANNs was collected from 71 subjects by applying examination protocols that were developed by experts in the appropriate fields. The diagnostic yield obtained by the examined models was in the region of 80 to 90%

Keywords

medical diagnostic computing; medical expert systems; neural nets; self-organising feature maps; artificial neural networks; integrated system; medical diagnosis; unsupervized self organizing feature maps algorithm; Artificial neural networks; Diseases; Genetics; Laboratories; Medical diagnosis; Muscles; Neuromuscular; Protocols; Spinal cord; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Biomedical Engineering Days, 1992., Proceedings of the 1992 International

Conference_Location

Istanbul

Print_ISBN

0-7803-0743-7

Type

conf

DOI

10.1109/IBED.1992.247114

Filename

247114

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3387048