-
Chapter and Conference Paper
Leverage Score Sampling for Complete Mode Coverage in Generative Adversarial Networks
Commonly, machine learning models minimize an empirical expectation. As a result, the trained models typically perform well for the majority of the data but the performance may deteriorate in less dense region...
-
Chapter
The Obligation of the de facto Director to Declare the State of Bankruptcy Under Belgian Criminal and Civil Law: Who’s Who and What’s What?
In this article we would like to discuss a topic which bears some concern to us. Belgian criminal law knows various so-called bankruptcy offences.
-
Article
Open AccessAn automated data cleaning method for Electronic Health Records by incorporating clinical knowledge
The use of Electronic Health Records (EHR) data in clinical research is incredibly increasing, but the abundancy of data resources raises the challenge of data cleaning. It can save time if the data cleaning c...
-
Article
Open AccessAn ensemble-based feature selection framework to select risk factors of childhood obesity for policy decision making
The increasing prevalence of childhood obesity makes it essential to study the risk factors with a sample representative of the population covering more health topics for better preventive policies and interve...
-
Article
Open AccessSpatially aware clustering of ion images in mass spectrometry imaging data using deep learning
Computational analysis is crucial to capitalize on the wealth of spatio-molecular information generated by mass spectrometry imaging (MSI) experiments. Currently, the spatial information available in MSI data ...
-
Chapter and Conference Paper
The Bures Metric for Generative Adversarial Networks
Generative Adversarial Networks (GANs) are performant generative methods yielding high-quality samples. However, under certain circumstances, the training of GANs can lead to mode collapse or mode drop**. To...
-
Article
Endurance Exercise Intervention Is Beneficial to Kidney Function in a Rat Model of Isolated Abdominal Venous Congestion: a Pilot Study
In this study, the effects of moderate intense endurance exercise on heart and kidney function and morphology were studied in a thoracic inferior vena cava constricted (IVCc) rat model of abdominal venous cong...
-
Article
Exercise intervention in hospitalized heart failure patients, with emphasis on congestion-related complications: a review
The importance of physical activity has become evident since a sedentary lifestyle drives cardiovascular disease progression and is associated with increased morbidity and mortality. The favorable effects of e...
-
Article
Open AccessCurrent animal models for the study of congestion in heart failure: an overview
Congestion (i.e., backward failure) is an important culprit mechanism driving disease progression in heart failure. Nevertheless, congestion remains often underappreciated and clinicians underestimate the impo...
-
Article
Open AccessSelective abdominal venous congestion induces adverse renal and hepatic morphological and functional alterations despite a preserved cardiac function
Venous congestion is an important contributor to worsening renal function in heart failure and the cardiorenal syndrome. In patients, it is difficult to study the effects of isolated venous congestion on organ...
-
Article
Open AccessACE-inhibition induces a cardioprotective transcriptional response in the metabolic syndrome heart
Cardiovascular disease associated with metabolic syndrome has a high prevalence, but the mechanistic basis of metabolic cardiomyopathy remains poorly understood. We characterised the cardiac transcriptome in a...
-
Article
Open AccessSoftware-guided versus nurse-directed blood glucose control in critically ill patients: the LOGIC-2 multicenter randomized controlled clinical trial
Blood glucose control in the intensive care unit (ICU) has the potential to save lives. However, maintaining blood glucose concentrations within a chosen target range is difficult in clinical practice and hold...
-
Article
Open AccessExternal Validation of a risk stratification model to assist shared decision making for patients starting renal replacement therapy
Shared decision making is nowadays acknowledged as an essential step when deciding on starting renal replacement therapy. Valid risk stratification of prognosis is, besides discussing quality of life, crucial ...
-
Article
Open AccessProblems with the nested granularity of feature domains in bioinformatics: the eXtasy case
Data from biomedical domains often have an inherit hierarchical structure. As this structure is usually implicit, its existence can be overlooked by practitioners interested in constructing and evaluating pred...
-
Article
Open AccessPredicting breast cancer using an expression values weighted clinical classifier
Clinical data, such as patient history, laboratory analysis, ultrasound parameters-which are the basis of day-to-day clinical decision support-are often used to guide the clinical management of cancer in the p...
-
Article
Open AccessNew bandwidth selection criterion for Kernel PCA: Approach to dimensionality reduction and classification problems
DNA microarrays are potentially powerful technology for improving diagnostic classification, treatment selection, and prognostic assessment. The use of this technology to predict cancer outcome has a history o...
-
Chapter
Biomarkers of Endometriosis
Endometriosis is a benign gynecological disease defined by the ectopic presence of endometrium and associated with pelvic pain and infertility. The etiology and pathogenesis remain unclear. The gold standard o...
-
Article
eXtasy: variant prioritization by genomic data fusion
By fusing genomic data, the eXtasy tool effectively prioritizes rare human exomic sequence variants as causal disease variants.
-
Chapter and Conference Paper
A Genetic Algorithm for Pancreatic Cancer Diagnosis
Pancreatic cancer is one of the leading causes of cancer-related death in the industrialized countries and it has the least favorable prognosis among various cancer types. In this study we aim to facilitate ea...
-
Chapter and Conference Paper
A Hybrid Approach to Feature Ranking for Microarray Data Classification
We present a novel approach to multivariate feature ranking in context of microarray data classification that employs a simple genetic algorithm in conjunction with Random forest feature importance measures. W...
