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Neural Network-Based Diagnosing for Optic Nerve Disease from Visual-Evoked Potential

机译:基于视觉诱发电位的基于神经网络的视神经疾病诊断

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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.
机译:在本文中,我们旨在采用一种诊断程序,使用人工神经网络(ANN)从视觉诱发电位(VEP)信号中识别视神经疾病。实现了使用Levenberg Marquart反向传播算法训练的多层前馈ANN。视神经疾病受试者的正确分类率为96.87%,健康受试者为96.66%。最终结果被分类为健康和患病。测试结果被发现符合医师直接诊断,血管造影,VEP和模式视网膜电图的预期结果。结果表明,该方法可以指出一种新型智能辅助诊断系统的设计能力。

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