Sobolewski P, Swiercz M, Grusza M, Stankiewicz A
Oddziału Okulistycznego Wojewódzkiego Szpitala Zespolonego w Suwałkach.
Klin Oczna. 1997;99(3):161-4.
The authors present the "pattern" visual evoked potentials (VEP) analysis with use of the artificial neural networks (ANN).
The study involved 11 patients with compressive chiasmal optic neuropathy, 20 patients with optic neuritis, 12 patients with anterior ischaemic optic neuropathy, 20 patients with optic nerve atrophy from neuritis, 8 patients with demyelinative neuropathy, 5 patients with oedema optic nerve, 20 healthy persons. The tests of visual evoked potentials were performed with the use of computer system UTAS-E1000. Classification of potentials was made by correlation of outputs of ANN with results of confirmed neuro-ophthalmology conditions.
ANN of different architecture were classified correctly in 80-100% of VEP record samples.
The obtained correctness of classification confirms usefulness of VEP analysis as the objective diagnostic method in some neuro-ophthalmological diseases and indicates application of ANN in multifactor analysis.
作者介绍了使用人工神经网络（ANN）进行“模式”视觉诱发电位（VEP）分析。
该研究纳入了11例压迫性视交叉视神经病变患者、20例视神经炎患者、12例前部缺血性视神经病变患者、20例神经炎所致视神经萎缩患者、8例脱髓鞘性神经病变患者、5例视神经水肿患者以及20名健康人。使用计算机系统UTAS-E1000进行视觉诱发电位测试。通过将人工神经网络的输出与确诊的神经眼科疾病结果进行关联，对电位进行分类。
不同结构的人工神经网络在80%至100%的VEP记录样本中分类正确。
所获得的分类正确性证实了VEP分析作为某些神经眼科疾病客观诊断方法的有用性，并表明人工神经网络在多因素分析中的应用。
