BACKGROUND The aim of this study is to develop a simple and reliable hybrid decision support model by combining statistical analysis and decision tree algorithms to ensure high accuracy of early diagnosis in patients with suspected acute appendicitis and to identify useful decision rules. METHODS We enrolled 326 patients who attended an emergency medical center complaining mainly of acute abd...

We propose several novel criteria for the selection of groups of jointly informative continuous features in the context of classification. Our approach is based on combining a Gaussian modeling of the feature responses, with derived upper bounds on their mutual information with the class label and their joint entropy. We further propose specific algorithmic implementations of these criteria whi...

We present a novel non-parametric method for finding a subspace of stimulus features that contains all information about the response of a system. Our method generalizes similar approaches to this problem such as spike triggered average, spike triggered covariance, or maximally informative dimensions. Instead of maximizing the mutual information between features and responses directly, we use i...

A new approach of constructing the similarity matrix for eigendecomposition on graph Laplacians is proposed. We first connect the Locality Preserving Projection method to probability density derivatives, which are then replaced by informative score vectors. This change yields a normalization factor and increases the contribution of the data pairs in low-density regions. The proposed method can ...

Microarray experiments are emerging as one of the main driving forces in modern biology. By allowing the simultaneous monitoring of the expression of the entire genome for a given organism, array experiments provide tremendous insight into the fundamental biological processes that translate genetic information. One of the major challenges is to identify computationally efficient and biologicall...