کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10323040 | 660888 | 2005 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Detection of femoral artery occlusion from spectral density of Doppler signals using the artificial neural network
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
This research is concentrated on the diagnosis of occlusion disease through the analysis of femoral artery Doppler signals with the help of Artificial Neural Network (ANN). Doppler femoral artery signals belong to occlusion patient and healthy subjects were recorded. Afterwards, power spectral densities (PSD) of these signals were obtained using Welch method and Autoregressive (AR) modeling. Multilayer feed forward ANN trained with a Levenberg Marquart (LM) backpropagation algorithm was implemented to these PSD. The designed classification structure has about 98% sensitivity, 97-100% specifity and correct classification is calculated to be 98-99% (for AR modeling and Welch method respectively). 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. The end benefit would be to assist the physician to make the final decision without hesitation.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 29, Issue 4, November 2005, Pages 945-952
Journal: Expert Systems with Applications - Volume 29, Issue 4, November 2005, Pages 945-952
نویسندگان
Sadik Kara, Semra KemaloÄlu, AyÅegül Güven,