Literature DB >> 18461817

Comparison of MLP neural network and neuro-fuzzy system in transcranial Doppler signals recorded from the cerebral vessels.

Firat Hardalaç1.   

Abstract

Transcranial Doppler signals recorded from cerebral vessels of 110 patients were transferred to a personal computer by using a 16 bit sound card. Spectral analyses of Transcranial Doppler signals were performed for determining the Multi Layer Perceptron (MLP) neural network and neuro Ankara-fuzzy system inputs. In order to do a good interpretation and rapid diagnosis, FFT parameters of Transcranial Doppler signals classified using MLP neural network and neuro-fuzzy system. Our findings demonstrated that 92% correct classification rate was obtained from MLP neural network, and 86% correct classification rate was obtained from neuro-fuzzy system.

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Year:  2008        PMID: 18461817     DOI: 10.1007/s10916-007-9116-6

Source DB:  PubMed          Journal:  J Med Syst        ISSN: 0148-5598            Impact factor:   4.460


  12 in total

1.  Obtaining interpretable fuzzy classification rules from medical data.

Authors:  D Nauck; R Kruse
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2.  Comparison of FFT and adaptive ARMA methods in transcranial Doppler signals recorded from the cerebral vessels.

Authors:  Inan Güler; Firat Hardalaç; Memduh Kaymaz
Journal:  Comput Biol Med       Date:  2002-11       Impact factor: 4.589

3.  Classification of carotid artery stenosis of patients with diabetes by neural network and logistic regression.

Authors:  U Uçman Ergün; Selami Serhatlioğlu; Firat Hardalaç; Inan Güler
Journal:  Comput Biol Med       Date:  2004-07       Impact factor: 4.589

4.  Modern spectral analysis techniques for blood flow velocity and spectral measurements with pulsed Doppler ultrasound.

Authors:  J Y David; S A Jones; D P Giddens
Journal:  IEEE Trans Biomed Eng       Date:  1991-06       Impact factor: 4.538

5.  Sequential versus standard neural networks for pattern recognition: an example using the domain of coronary heart disease.

Authors:  L Ohno-Machado; M A Musen
Journal:  Comput Biol Med       Date:  1997-07       Impact factor: 4.589

Review 6.  Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine.

Authors:  M H Zweig; G Campbell
Journal:  Clin Chem       Date:  1993-04       Impact factor: 8.327

7.  Artificial neural network analysis of common femoral artery Doppler shift signals: classification of proximal disease.

Authors:  I A Wright; N A Gough
Journal:  Ultrasound Med Biol       Date:  1999-06       Impact factor: 2.998

8.  The application of an artificial neural network to Doppler ultrasound waveforms for the classification of arterial disease.

Authors:  J H Smith; J Graham; R J Taylor
Journal:  Int J Clin Monit Comput       Date:  1996-05

9.  Classification of transcranial Doppler signals using artificial neural network.

Authors:  Selami Serhatlioğlu; Firat Hardalaç; Inan Güler
Journal:  J Med Syst       Date:  2003-04       Impact factor: 4.460

10.  Application of FFT analyzed cardiac Doppler signals to fuzzy algorithm.

Authors:  Inan Güler; Firat Hardalaç; Necaattin Barişçi
Journal:  Comput Biol Med       Date:  2002-11       Impact factor: 4.589

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  1 in total

1.  Comparing methods for determining motor-hand lateralization based on fTCD signals.

Authors:  Walter H L Pinaya; Francisco J Fraga; Salo S Haratz; Philip J A Dean; Adriana B Conforto; Edson Bor-Seng-Shu; Manoel J Teixeira; João R Sato
Journal:  J Med Syst       Date:  2015-01-27       Impact factor: 4.460

  1 in total

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