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Institution

Radboud University Nijmegen

EducationNijmegen, Gelderland, Netherlands
About: Radboud University Nijmegen is a education organization based out in Nijmegen, Gelderland, Netherlands. It is known for research contribution in the topics: Population & Randomized controlled trial. The organization has 35417 authors who have published 83035 publications receiving 3285064 citations. The organization is also known as: Catholic University of Nijmegen & Radboud University.


Papers
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Journal ArticleDOI
Martine Hoogman1, Janita Bralten1, Derrek P. Hibar2, Maarten Mennes, Marcel P. Zwiers, Lizanne S.J. Schweren3, Kimm J. E. van Hulzen1, Sarah E. Medland4, Elena Shumskaya1, Neda Jahanshad2, Patrick de Zeeuw5, Eszter Szekely6, Gustavo Sudre6, Thomas Wolfers1, Alberdingk M.H. Onnink1, Janneke Dammers1, Jeanette C. Mostert1, Yolanda Vives-Gilabert, Gregor Kohls, Eileen Oberwelland, Jochen Seitz, Martin Schulte-Rüther, Sara Ambrosino5, Alysa E. Doyle7, Alysa E. Doyle8, Marie F. Høvik9, Margaretha Dramsdahl10, Leanne Tamm11, Theo G.M. van Erp12, Anders M. Dale13, Andrew J. Schork13, Annette Conzelmann14, Annette Conzelmann15, Kathrin C. Zierhut15, Ramona Baur15, Hazel McCarthy16, Yuliya N. Yoncheva17, Ana Cubillo18, Kaylita Chantiluke18, Mitul A. Mehta18, Yannis Paloyelis18, Sarah Hohmann19, Sarah Baumeister19, Ivanei E. Bramati, Paulo Mattos20, Fernanda Tovar-Moll20, Pamela K. Douglas21, Tobias Banaschewski19, Daniel Brandeis, Jonna Kuntsi18, Philip Asherson18, Katya Rubia18, Clare Kelly17, Clare Kelly16, Adriana Di Martino17, Michael P. Milham22, Michael P. Milham23, Francisco X. Castellanos22, Francisco X. Castellanos17, Thomas Frodl16, Thomas Frodl24, Mariam Zentis24, Klaus-Peter Lesch15, Klaus-Peter Lesch25, Andreas Reif26, Paul Pauli15, Terry L. Jernigan13, Jan Haavik9, Jan Haavik27, Kerstin J. Plessen, Astri J. Lundervold9, Kenneth Hugdahl27, Kenneth Hugdahl9, Larry J. Seidman7, Larry J. Seidman28, Joseph Biederman7, Nanda Rommelse1, Dirk J. Heslenfeld29, Catharina A. Hartman3, Pieter J. Hoekstra3, Jaap Oosterlaan29, Georg von Polier, Kerstin Konrad, Oscar Vilarroya30, Josep Antoni Ramos-Quiroga30, Joan Carles Soliva30, Sarah Durston5, Jan K. Buitelaar1, Stephen V. Faraone31, Stephen V. Faraone9, Philip Shaw6, Paul M. Thompson2, Barbara Franke1 
TL;DR: Lifespan analyses suggest that, in the absence of well powered longitudinal studies, the ENIGMA cross-sectional sample across six decades of ages provides a means to generate hypotheses about lifespan trajectories in brain phenotypes.

749 citations

Journal ArticleDOI
TL;DR: Identification of optimal machine-learning methods for radiomic applications is a crucial step towards stable and clinically relevant radiomic biomarkers, providing a non-invasive way of quantifying and monitoring tumor-phenotypic characteristics in clinical practice.
Abstract: Radiomics extracts and mines large number of medical imaging features quantifying tumor phenotypic characteristics Highly accurate and reliable machine-learning approaches can drive the success of radiomic applications in clinical care In this radiomic study, fourteen feature selection methods and twelve classification methods were examined in terms of their performance and stability for predicting overall survival A total of 440 radiomic features were extracted from pre-treatment computed tomography (CT) images of 464 lung cancer patients To ensure the unbiased evaluation of different machine-learning methods, publicly available implementations along with reported parameter configurations were used Furthermore, we used two independent radiomic cohorts for training (n = 310 patients) and validation (n = 154 patients) We identified that Wilcoxon test based feature selection method WLCX (stability = 084 ± 005, AUC = 065 ± 002) and a classification method random forest RF (RSD = 352%, AUC = 066 ± 003) had highest prognostic performance with high stability against data perturbation Our variability analysis indicated that the choice of classification method is the most dominant source of performance variation (3421% of total variance) Identification of optimal machine-learning methods for radiomic applications is a crucial step towards stable and clinically relevant radiomic biomarkers, providing a non-invasive way of quantifying and monitoring tumor-phenotypic characteristics in clinical practice

749 citations

Journal ArticleDOI
TL;DR: A review of new developments in theoretical and experimental electronic-structure investigations of half-metallic ferromagnets (HMFs) is presented in this article, where the effects of electron-magnon interaction in HMFs and their manifestations in magnetic, spectral, thermodynamic, and transport properties are considered.
Abstract: A review of new developments in theoretical and experimental electronic-structure investigations of half-metallic ferromagnets (HMFs) is presented. Being semiconductors for one spin projection and metals for another, these substances are promising magnetic materials for applications in spintronics (i.e., spin-dependent electronics). Classification of HMFs by the peculiarities of their electronic structure and chemical bonding is discussed. The effects of electron-magnon interaction in HMFs and their manifestations in magnetic, spectral, thermodynamic, and transport properties are considered. Special attention is paid to the appearance of nonquasiparticle states in the energy gap, which provide an instructive example of essentially many-body features in the electronic structure. State-of-the-art electronic calculations for correlated d-systems are discussed, and results for specific HMFs (Heusler alloys, zinc-blende structure compounds, CrO2, and Fe3O4) are reviewed.

748 citations

Journal ArticleDOI
TL;DR: Obeticholic acid administered with ursodiol or as monotherapy for 12 months in patients with primary biliary cholangitis resulted in decreases from baseline in alkaline phosphatase and total bilirubin levels that differed significantly from the changes observed with placebo.
Abstract: Background Primary biliary cholangitis (formerly called primary biliary cirrhosis) can progress to cirrhosis and death despite ursodiol therapy. Alkaline phosphatase and bilirubin levels correlate with the risk of liver transplantation or death. Obeticholic acid, a farnesoid X receptor agonist, has shown potential benefit in patients with this disease. Methods In this 12-month, double-blind, placebo-controlled, phase 3 trial, we randomly assigned 217 patients who had an inadequate response to ursodiol or who found the side effects of ursodiol unacceptable to receive obeticholic acid at a dose of 10 mg (the 10-mg group), obeticholic acid at a dose of 5 mg with adjustment to 10 mg if applicable (the 5-10-mg group), or placebo. The primary end point was an alkaline phosphatase level of less than 1.67 times the upper limit of the normal range, with a reduction of at least 15% from baseline, and a normal total bilirubin level. Results Of 216 patients who underwent randomization and received at least one dose of obeticholic acid or placebo, 93% received ursodiol as background therapy. The primary end point occurred in more patients in the 5-10-mg group (46%) and the 10-mg group (47%) than in the placebo group (10%; P Conclusions Obeticholic acid administered with ursodiol or as monotherapy for 12 months in patients with primary biliary cholangitis resulted in decreases from baseline in alkaline phosphatase and total bilirubin levels that differed significantly from the changes observed with placebo. There were more serious adverse events with obeticholic acid. (Funded by Intercept Pharmaceuticals; POISE ClinicalTrials.gov number, NCT01473524; Current Controlled Trials number, ISRCTN89514817.).

747 citations

Journal ArticleDOI
TL;DR: A large-scale study with Dutch and Korean speakers of L2 English tested whether LexTALE, a 5-min vocabulary test, is a valid predictor of English vocabulary knowledge and, possibly, even of general English proficiency and showed that it was generally superior to self-ratings in its predictions.
Abstract: The increasing number of experimental studies on second language (L2) processing, frequently with English as the L2, calls for a practical and valid measure of English vocabulary knowledge and proficiency. In a large-scale study with Dutch and Korean speakers of L2 English, we tested whether LexTALE, a 5-min vocabulary test, is a valid predictor of English vocabulary knowledge and, possibly, even of general English proficiency. Furthermore, the validity of LexTALE was compared with that of self-ratings of proficiency, a measure frequently used by L2 researchers. The results showed the following in both speaker groups: (1) LexTALE was a good predictor of English vocabulary knowledge; 2) it also correlated substantially with a measure of general English proficiency; and 3) LexTALE was generally superior to self-ratings in its predictions. LexTALE, but not self-ratings, also correlated highly with previous experimental data on two word recognition paradigms. The test can be carried out on or downloaded from www.lextale.com.

745 citations


Authors

Showing all 35749 results

NameH-indexPapersCitations
Charles A. Dinarello1901058139668
Richard H. Friend1691182140032
Yang Gao1682047146301
Ian J. Deary1661795114161
David T. Felson153861133514
Margaret A. Pericak-Vance149826118672
Fernando Rivadeneira14662886582
Shah Ebrahim14673396807
Mihai G. Netea142117086908
Mingshui Chen1411543125369
George Alverson1401653105074
Barry Blumenfeld1401909105694
Harvey B Newman139159488308
Tariq Aziz138164696586
Stylianos E. Antonarakis13874693605
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023123
2022492
20216,380
20206,080
20195,747
20185,114