论文信息 - Self organizing neural network approach for identification of patients with Congestive Heart Failure

Self organizing neural network approach for identification of patients with Congestive Heart Failure

A new technique for identification of patients with Congestive Heart Failure (CHF) from normal controls is investigated in this paper using spectral analysis and neural networks. The data used in this work is obtained from Massachusetts Institute of Technology (MIT) databases. A data set of 17 CHF and 53 normal subjects is used as original learning data set. A larger learning data set, which is obtained by simulating 1000 CHF and 1000 normal subjects according to the spectral features obtained from the original learning data, is used by the self organizing neural network.

Nazar Elfadil | Intisar Ibrahim

[1] Jian-Hua Zhang,et al. A nonlinear adaptive fuzzy approximator technique with its application to prediction of non-stationary EEG dynamics and estimation of single-sweep evoked potentials. , 2005, Technology and health care : official journal of the European Society for Engineering and Medicine.

[2] Teuvo Kohonen,et al. Self-Organizing Maps , 2010 .

[3] Abdulnasir Hossen,et al. Identification of patients with congestive heart failure using different neural networks approaches. , 2009, Technology and health care : official journal of the European Society for Engineering and Medicine.

[4] Nazar Elfadil. Machine Learning: Automated Knowledge Acquisition Based on Unsupervised Neural Network and Expert System Paradigms , 2005, J. Adv. Comput. Intell. Intell. Informatics.

[5] Abdulnasir Hossen,et al. A New Method For Screening Of Patients With Congestive Heart Failure , 2004, International Conference on Computational Intelligence.

[6] M. V. Velzen,et al. Self-organizing maps , 2007 .

[7] A. Malliani,et al. Heart rate variability. Standards of measurement, physiological interpretation, and clinical use , 1996 .