Neural computing: an introduction
Neural computing: an introduction
Introduction to the Analysis and Processing of Signals
Introduction to the Analysis and Processing of Signals
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Artificial Neural Networks in Biomedicine
Artificial Neural Networks in Biomedicine
Training a learning vector quantization network using the pattern electroretinography signals
Computers in Biology and Medicine
Computers in Biology and Medicine
Utilization of artificial neural networks in the diagnosis of optic nerve diseases
Computers in Biology and Medicine
Expert Systems with Applications: An International Journal
Medical informatics: reasoning methods
Artificial Intelligence in Medicine
Journal of Medical Systems
Utilization of Discretization method on the diagnosis of optic nerve disease
Computer Methods and Programs in Biomedicine
Review article: Human scalp EEG processing: Various soft computing approaches
Applied Soft Computing
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In this paper, we purpose a diagnostic procedure to identify the optic nerve disease from visual evoked potential (VEP) signals using an Artificial Neural Network (ANN). Multilayer feed forward ANN trained with a Levenberg Marquart backpropagation algorithm was implemented. The correct classification rate was 96.87% for subjects having optic nerve disease and 96.66% for healthy subjects. The end results are classified as healthy and diseased. Testing results were found to be compliant with the expected results that are derived from the physician's direct diagnosis, angiography, VEP and pattern electroretinography. The stated results show that the proposed method could point out the ability of design of a new intelligent assistance diagnosis system.