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Institution

Katholieke Universiteit Leuven

EducationLeuven, Belgium
About: Katholieke Universiteit Leuven is a education organization based out in Leuven, Belgium. It is known for research contribution in the topics: Population & Transplantation. The organization has 61109 authors who have published 176584 publications receiving 6210872 citations.


Papers
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Journal ArticleDOI
TL;DR: Ustekinumab induced a clinical response in patients with moderate-to-severe Crohn's disease, especially in patients previously given infliximab.

727 citations

Journal ArticleDOI
TL;DR: The Gini importance of the random forest provided superior means for measuring feature relevance on spectral data, but – on an optimal subset of features – the regularized classifiers might be preferable over the random Forest classifier, in spite of their limitation to model linear dependencies only.
Abstract: Regularized regression methods such as principal component or partial least squares regression perform well in learning tasks on high dimensional spectral data, but cannot explicitly eliminate irrelevant features. The random forest classifier with its associated Gini feature importance, on the other hand, allows for an explicit feature elimination, but may not be optimally adapted to spectral data due to the topology of its constituent classification trees which are based on orthogonal splits in feature space. We propose to combine the best of both approaches, and evaluated the joint use of a feature selection based on a recursive feature elimination using the Gini importance of random forests' together with regularized classification methods on spectral data sets from medical diagnostics, chemotaxonomy, biomedical analytics, food science, and synthetically modified spectral data. Here, a feature selection using the Gini feature importance with a regularized classification by discriminant partial least squares regression performed as well as or better than a filtering according to different univariate statistical tests, or using regression coefficients in a backward feature elimination. It outperformed the direct application of the random forest classifier, or the direct application of the regularized classifiers on the full set of features. The Gini importance of the random forest provided superior means for measuring feature relevance on spectral data, but – on an optimal subset of features – the regularized classifiers might be preferable over the random forest classifier, in spite of their limitation to model linear dependencies only. A feature selection based on Gini importance, however, may precede a regularized linear classification to identify this optimal subset of features, and to earn a double benefit of both dimensionality reduction and the elimination of noise from the classification task.

726 citations

Journal ArticleDOI
TL;DR: The past, present, and future therapies to reduce ischemia/reperfusion injury are examined; few interventions have successfully passed the proof-of-concept stage.

726 citations

Journal ArticleDOI
TL;DR: These European Society for Clinical Microbiology and Infectious Diseases and European Confederation of Medical Mycology Joint Clinical Guidelines focus on the diagnosis and management of mucormycosis and strongly recommend continuing treatment until complete response demonstrated on imaging and permanent reversal of predisposing factors.

725 citations

Journal ArticleDOI
TL;DR: It is concluded that TET2 is the most frequently mutated gene in MDS known so far, and expression was shown to be elevated in hematopoietic cells with highest expression in granulocytes, in line with a function in myelopoiesis.
Abstract: Myelodysplastic syndromes (MDS) represent a heterogeneous group of neoplastic hematopoietic disorders. Several recurrent chromosomal aberrations have been associated with MDS, but the genes affected have remained largely unknown. To identify relevant genetic lesions involved in the pathogenesis of MDS, we conducted SNP array-based genomic profiling and genomic sequencing in 102 individuals with MDS and identified acquired deletions and missense and nonsense mutations in the TET2 gene in 26% of these individuals. Using allele-specific assays, we detected TET2 mutations in most of the bone marrow cells (median 96%). In addition, the mutations were encountered in various lineages of differentiation including CD34(+) progenitor cells, suggesting that TET2 mutations occur early during disease evolution. In healthy tissues, TET2 expression was shown to be elevated in hematopoietic cells with highest expression in granulocytes, in line with a function in myelopoiesis. We conclude that TET2 is the most frequently mutated gene in MDS known so far.

725 citations


Authors

Showing all 61602 results

NameH-indexPapersCitations
Eugene Braunwald2301711264576
Joseph L. Goldstein207556149527
Rakesh K. Jain2001467177727
Stefan Schreiber1781233138528
Masayuki Yamamoto1711576123028
Jun Wang1661093141621
David R. Jacobs1651262113892
Klaus Müllen1642125140748
Peter Carmeliet164844122918
Hua Zhang1631503116769
William J. Sandborn1621317108564
Elliott M. Antman161716179462
Tobin J. Marks1591621111604
Ian A. Wilson15897198221
Johan Auwerx15865395779
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023307
2022857
202111,007
202010,541
20199,719
20189,532