Sara Moein

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In this paper, application of artificial neural networks in typical disease diagnosis has been investigated. The real procedure of medical diagnosis which usually is employed by physicians was analyzed and converted to a machine implementable format. Then after selecting some symptoms of eight different diseases, a data set contains the information of a few(More)
  • Sara Moein
  • Advances in experimental medicine and biology
  • 2010
In this paper, application of Artificial Neural Network (ANN) for electrocardiogram (ECG) signal noise removal has been investigated. First, 100 number of ECG signals are selected from Physikalisch-Technische Bundesanstalt (PTB) database and Kalman filter is applied to remove their low pass noise. Then a suitable dataset based on denoised ECG signal is(More)
Electrocardiogram (ECG) is an important biomedical tool for the diagnosis of heart disorders. However, the signal is susceptible to noise and it is essential to remove the noise especially when undertaking automated processing of the signal. In this paper, an intelligent approach based on moving median filter and Self-Organizing Map (SOM) neural network is(More)
In this paper, an automated approach for electrocardiogram (ECG) signal noise removing using artificial neural network is investigated. First, 150 of noisy heart signal are collected form MIT-BIH database. Then signals are transformed to frequency domain and cutoff frequency is calculated. Since heart signals are lowpass frequency, a Finite Impulse Response(More)