On the overestimation of random forest’s out-of-bag error S Janitza, R Hornung PloS one 13 (8), e0201904, 2018 | 216 | 2018 |
Large-scale benchmark study of survival prediction methods using multi-omics data M Herrmann, P Probst, R Hornung, V Jurinovic, AL Boulesteix Briefings in bioinformatics 22 (3), bbaa167, 2021 | 68 | 2021 |
The impact of continuous non-invasive arterial blood pressure monitoring on blood pressure stability during general anaesthesia in orthopaedic patients: a randomised trial AS Meidert, JS Nold, R Hornung, AC Paulus, B Zwißler, S Czerner European Journal of Anaesthesiology| EJA 34 (11), 716-722, 2017 | 64 | 2017 |
Ordinal forests R Hornung Journal of Classification 37 (1), 4-17, 2020 | 59 | 2020 |
Priority-Lasso: a simple hierarchical approach to the prediction of clinical outcome using multi-omics data S Klau, V Jurinovic, R Hornung, T Herold, AL Boulesteix BMC bioinformatics 19, 1-14, 2018 | 53 | 2018 |
Combining location-and-scale batch effect adjustment with data cleaning by latent factor adjustment R Hornung, AL Boulesteix, D Causeur BMC bioinformatics 17, 1-19, 2016 | 45 | 2016 |
Introduction to statistical simulations in health research AL Boulesteix, RHH Groenwold, M Abrahamowicz, H Binder, M Briel, ... BMJ open 10 (12), e039921, 2020 | 34 | 2020 |
Block Forests: random forests for blocks of clinical and omics covariate data R Hornung, MN Wright BMC Bioinformatics 20, 358, 2019 | 33 | 2019 |
Improving cross-study prediction through addon batch effect adjustment or addon normalization R Hornung, D Causeur, C Bernau, AL Boulesteix Bioinformatics 33 (3), 397-404, 2017 | 25 | 2017 |
OrdinalForest: Ordinal forests: Prediction and variable ranking with ordinal target variables R Hornung R package version 2, 2018 | 22 | 2018 |
Evaluating the best empirical antibiotic therapy in patients with acute-on-chronic liver failure and spontaneous bacterial peritonitis A Wieser, H Li, J Zhang, I Liss, D Markwardt, R Hornung, S Suerbaum, ... Digestive and Liver Disease 51 (9), 1300-1307, 2019 | 20 | 2019 |
Patients with cirrhosis and SBP: Increase in multidrug‐resistant organisms and complications H Li, A Wieser, J Zhang, I Liss, D Markwardt, R Hornung, ... European Journal of Clinical Investigation 50 (2), e13198, 2020 | 19 | 2020 |
A measure of the impact of CV incompleteness on prediction error estimation with application to PCA and normalization R Hornung, C Bernau, C Truntzer, R Wilson, T Stadler, AL Boulesteix BMC Medical Research Methodology 15, 1-15, 2015 | 19 | 2015 |
Making complex prediction rules applicable for readers: Current practice in random forest literature and recommendations AL Boulesteix, S Janitza, R Hornung, P Probst, H Busen, A Hapfelmeier Biometrical Journal 61 (5), 1314-1328, 2019 | 15 | 2019 |
Interaction forests: Identifying and exploiting interpretable quantitative and qualitative interaction effects R Hornung, AL Boulesteix Computational Statistics & Data Analysis 171, 107460, 2022 | 14 | 2022 |
Benchmark study of feature selection strategies for multi-omics data Y Li, U Mansmann, S Du, R Hornung BMC bioinformatics 23 (1), 412, 2022 | 13 | 2022 |
Complement C3 identified as a unique risk factor for disease severity among young COVID-19 patients in Wuhan, China W Cheng, R Hornung, K Xu, CH Yang, J Li Scientific Reports 11 (1), 7857, 2021 | 13 | 2021 |
Mediation analysis reveals common mechanisms of RUNX1 point mutations and RUNX1/RUNX1T1 fusions influencing survival of patients with acute myeloid … R Hornung, V Jurinovic, AMN Batcha, SA Bamopoulos, ... Scientific Reports 8 (1), 11293, 2018 | 13 | 2018 |
A u-statistic estimator for the variance of resampling-based error estimators M Fuchs, R Hornung, R De Bin, AL Boulesteix arXiv preprint arXiv:1310.8203, 2013 | 13 | 2013 |
Efficient permutation testing of variable importance measures by the example of random forests A Hapfelmeier, R Hornung, B Haller Computational Statistics & Data Analysis 181, 107689, 2023 | 11 | 2023 |