Use of artificial neural networks for clinical decision-making (Maldescensus testis)

Author

Papadourakis, George M. ; Gaga, Eleni ; Vareltzis, George ; Bebis, George

Author_Institution

Dept. of Comput. Sci., Crete Univ., Heraklion, Greece

Volume

3

fYear

1992

fDate

7-11 Jun 1992

Firstpage

159

Abstract

The application of artificial neural networks (ANNs) to medical diagnosis and in particular for the Maldescensus testis domain is presented. Various architectures and schemes using the traditional backpropagation are considered. The input data to the neural networks were encoded in two different ways, that is, using real values and gray code representation. These different architectures and schemes were evaluated and compared in terms of classification accuracy and speed

Keywords

decision support systems; medical diagnostic computing; medical expert systems; neural nets; Maldescensus testis; artificial neural networks; classification accuracy; classification speed; clinical decision-making; gray code representation; medical diagnosis; real values; undescended testicle; Artificial intelligence; Artificial neural networks; Back; Computer science; Decision making; Medical diagnosis; Medical diagnostic imaging; Medical tests; Neural networks; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 1992. IJCNN., International Joint Conference on

Conference_Location

Baltimore, MD

Print_ISBN

0-7803-0559-0

Type

conf

DOI

10.1109/IJCNN.1992.227176

Filename

227176