Neural computing: an introduction
Neural computing: an introduction
Introduction to the Analysis and Processing of Signals
Introduction to the Analysis and Processing of Signals
Artificial Neural Networks in Biomedicine
Artificial Neural Networks in Biomedicine
Neural Networks: A Comprehensive Foundation (3rd Edition)
Neural Networks: A Comprehensive Foundation (3rd Edition)
Neural Network-Based Diagnosing for Optic Nerve Disease from Visual-Evoked Potential
Journal of Medical Systems
Utilization of Discretization method on the diagnosis of optic nerve disease
Computer Methods and Programs in Biomedicine
Detection of Carotid Artery Disease by Using Learning Vector Quantization Neural Network
Journal of Medical Systems
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In this study, the pattern electroretinography (PERG) signals derived from evoked potential across retinal cells of subjects after visual stimulation were analyzed using artificial neural network (ANN) with 172 healthy and 148 diseased subjects. ANN was employed to PERG signals to distinguish between healthy eye and diseased eye. Supervised network examined was a competitive learning vector quantization network. The designed classification structure has about 94% sensitivity, 90.32% specifity, 5.94% false negative, 9.67% false positive and correct classification is calculated to be 92%. Testing results were found to be compliant with the expected results that are derived from the physician's direct diagnosis. The end benefit would be to assist the physician to make the final decision without hesitation.