Title :
A neural network expert system for diagnosing eye diseases
Author :
Syiam, Mostafa Mahmoud
Author_Institution :
Fac. of Electron. Eng., Menoufia Univ., Egypt
Abstract :
Presents a neural network expert system to assist a GP in early medical diagnosis of eye diseases in patients. The developed system bases its diagnosis on patient symptoms and signs, and uses a multilayer feedforward network with a single hidden layer. The backpropagation algorithm is employed for training the network in a supervised mode. The effect of the number of nodes in the hidden layer on the developed system´s performance is discussed. Analysis of the results indicates that the developed system has a disease diagnosis ratio of above 87 percent. To evaluate the performance of the developed system, a test data set was given to both GPs and specialists. It is indicated that the performance of the developed system exceeds that of the GPs, and it reaches the level of performance of the eye specialists
Keywords :
backpropagation; eye; feedforward neural nets; medical diagnostic computing; medical expert systems; performance evaluation; backpropagation algorithm; eye disease diagnosis; eye specialists; general practitioners; hidden layer nodes; medicine; multilayer feedforward network; neural network expert system; patient symptoms; performance evaluation; supervised mode; system performance; training; Backpropagation algorithms; Diagnostic expert systems; Diseases; Knowledge based systems; Medical diagnosis; Medical diagnostic imaging; Medical expert systems; Multi-layer neural network; Neural networks; System testing;
Conference_Titel :
Artificial Intelligence for Applications, 1994., Proceedings of the Tenth Conference on
Conference_Location :
San Antonia, TX
Print_ISBN :
0-8186-5550-X
DOI :
10.1109/CAIA.1994.323624
