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In this paper, we propose an efficient parameter tuning-free squared-loss mutual information (SMI) estimator in a form of a radial basis function (RBF) network. The input layer of the proposed network propagates a sample pair of two random variables to the hidden layer. The propagated samples are then transformed by a set of Gaussian RBF kernels with randomly determined kernel centers and widths similar...
Heart rate variability (HRV) is a non-invasive measurement that has shown promise as an indicator of cardiovascular, respiratory and metabolic dynamics. In this study, three different classification techniques, i.e. extreme learning machine (ELM), support vector machine (SVM) and back-propagation based neural network (BP), were investigated to classify HRV signals obtained from electrocardiograms...
To explore the use of pre-hospital heart rate variability (HRV) as a predictor of clinical outcomes such as hospital admission, intensive care unit (ICU) admission and mortality. We also implemented an automated pre-analysis signal processing algorithm and multiple principal component analysis (PCA) for outcomes.We conducted a prospective observational clinical study at an emergency medical services...
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