An artificial neural network ensemble is a learning paradigm where several artificial neural networks are jointly used to solve a problem. In this paper, an automatic pathological...
Abstract. This study aims to recover transient, trialvarying evoked potentials (EPs), in particular the movement-related potentials (MRPs), embedded within the background cerebral ...
D. D. Ben Dayan Rubin, G. Baselli, Gideon F. Inbar...
Background: Thousands of genes in a genomewide data set are tested against some null hypothesis, for detecting differentially expressed genes in microarray experiments. The expect...
Background: Microarray data normalization is an important step for obtaining data that are reliable and usable for subsequent analysis. One of the most commonly utilized normaliza...
John A. Berger, Sampsa Hautaniemi, Anna-Kaarina J&...
Background: This paper presents the use of Support Vector Machines (SVMs) for prediction and analysis of antisense oligonucleotide (AO) efficacy. The collected database comprises ...
Gustavo Camps-Valls, Alistair M. Chalk, Antonio J....