In clusters analysis, a problem of great interest is having methods that allow the representation of the topology of input space without the need to know additional information about it. This gives rise to growing competitive neural methods which are …
Support Vector Machines (SVM) have been applied extensively to classification and regression problems, but there are few solutions proposed for problems involving time-series. To evaluate their potential, a problem of difficult solution in the field …
Recent advances in digital processing of biological signals have made it possible to incorporate more extensive signals, generating a large number of features that must be analyzed to carry out the detection, and thereby acting against the …
Generally, discontinuity detection in automated visual testing consists of two steps: identification of potential discontinuities using image processing techniques and classification of potential discontinuities into discontinuities and regular …
This paper compares the classification performance of linear-system- and neural-network-based models in handwritten-digit classification and face recognition. In inputs to a linear classifier, nonlinear inputs are generated based on linear inputs, …
The function of the Cerebral Blood Flow Autoregulation (CBFA) system is to maintain a relatively constant flow of blood to the brain, in spite of changes in arterial blood pressure. A model that characterizes this system is of great use in …
This study presents the application of Bayesian networks (Bn) to explain Neonatal Intensive Care Unit relationships. Information was compiled retrospectively from the medical records at two neonatal intensive care units of 523 neonates (63 deaths). A …
The automatic detection of flaws through non-destructive testing uses pattern recognition methodology with binary classification. In this problem a decision is made about whether or not an initially segmented hypothetical flaw in an image is in fact …
A time lagged recurrent neural network (TLRN) was implemented to model the dynamic relationship between arterial blood pressure (ABP) and cerebral blood flow velocity (CBFV) and its performance was compared to classical linear model such as transfer …
Knowing a patient's risk at the moment of admission to a medical unit is important for both clinical and administrative decision making: it is fundamental to carry out a health technology assessment. In this paper, we propose a non-supervised …