Trung, Dung Tran; Lesaffre, Emmanuel; Verbeke, Geert; Molenberghs, Geert; 56633;
We propose a latent linear mixed model to analyze multivariate longitudinal data of multiple ordinal variables, which are manifestations of fewer continuous latent variables. We focus on the latent level where the effects of observed covariates on the latent variables are of interest. We incorporate serial correlation into the variance component ra...
Galaris, Evangelos; Gallos, Ioannis; Myatchin, Ivan; Lagae, Lieven; 18472; Siettos, Constantinos;
We localize the sources of brain activity of children with epilepsy based on electroencephalograph (EEG) recordings acquired during a visual discrimination working memory task. For the numerical solution of the inverse problem, with the aid of age-specific MRI scans processed from a publicly available database, we use and compare three regularizati...
Coppens, Lucas; Lavigne, Rob; 24787;
BACKGROUND: In silico promoter prediction represents an important challenge in bioinformatics as it provides a first-line approach to identifying regulatory elements to support wet-lab experiments. Historically, available promoter prediction software have focused on sigma factor-associated promoters in the model organism E. coli. As a consequence, ...
Hemptinne, Coralie; Deravet, Nicolas; de Xivry, Jean-Jacques Orban; 99946; Lefevre, Philippe; Yueksel, Demet;
This study analyzed the characteristics of pursuit and assessed the influence of prior and visual information on eye velocity and saccades in amblyopic and control children, in comparison to adults. Eye movements of 41 children (21 amblyopes and 20 controls) were compared to eye movements of 55 adults (18 amblyopes and 37 controls). Participants we...
Meyvisch, Paul; Alonso, Ariel; 65129; Van der Elst, Wim; Molenberghs, Geert; 56633;
The relationship between association and surrogacy has been the focus of much debate in the surrogate marker literature. Recently, the individual causal association (ICA) has been introduced as a metric of surrogacy in the causal inference framework, when both the surrogate and the true endpoint are normally distributed and when both are binary. Ea...
Chong, MY Gu, B Chan, BT Ong, ZC Xu, XY Lim, E
A monolithic, fully coupled fluid-structure interaction (FSI) computational framework was developed to account for dissection flap motion in acute type B aortic dissection (TBAD). Analysis of results included wall deformation, pressure, flow, wall shear stress (WSS), von. Mises stress and comparison of hemodynamics between rigid wall and FSI models...
Tabibian, Ashkan; 88513; Ghaffari, Siavash; Vargas, Diego A; Van Oosterwyck, Hans; 30372; Jones, Elizabeth A; 90875;
Shear stress induces directed endothelial cell (EC) migration in blood vessels leading to vessel diameter increase and induction of vascular maturation. Other factors, such as EC elongation and interaction between ECs and non-vascular areas are also important. Computational models have previously been used to study collective cell migration. These ...
Xu, X Manchester, E
The Food and Drug Administration's (FDA) benchmark nozzle model has been studied extensively both experimentally and computationally. Although considerable efforts have been made on validations of a variety of numerical models against available experimental data, the transitional flow cases are still not fully resolved, especially with regards to d...
Huang, Yuanzhi; Gilmour, Steven G; Mylona, Kalliopi; Goos, Peter; 6560;
status: published
Debeer, Dries; 67731; Strobl, Carolin;
BACKGROUND: Random forest based variable importance measures have become popular tools for assessing the contributions of the predictor variables in a fitted random forest. In this article we reconsider a frequently used variable importance measure, the Conditional Permutation Importance (CPI). We argue and illustrate that the CPI corresponds to a ...