کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
506192 864576 2007 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Training a learning vector quantization network using the pattern electroretinography signals
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
پیش نمایش صفحه اول مقاله
Training a learning vector quantization network using the pattern electroretinography signals
چکیده انگلیسی

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.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers in Biology and Medicine - Volume 37, Issue 1, January 2007, Pages 77–82
نویسندگان
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