Combining location-and-scale batch effect adjustment with data cleaning by latent factor adjustment. - Roman Hornung; Anne-Laure Boulesteix; David Causeur (BMC Bioinform., 2016)

Improving cross-study prediction through addon batch effect adjustment or addon normalization. - Roman Hornung; David Causeur; Christoph Bernau; Anne-Laure Boulesteix (Bioinform., 2017)

Priority-Lasso: a simple hierarchical approach to the prediction of clinical outcome using multi-omics data. - Simon Klau; Vindi Jurinovic; Roman Hornung; Tobias Herold; Anne-Laure Boulesteix (BMC Bioinform., 2018)

Block Forests: random forests for blocks of clinical and omics covariate data. - Roman Hornung; Marvin N. Wright (BMC Bioinform., 2019)

Ordinal Forests. - Roman Hornung (J. Classif., 2020)

Large-scale benchmark study of survival prediction methods using multi-omics data. - Moritz Herrmann; Philipp Probst; Roman Hornung; Vindi Jurinovic; Anne-Laure Boulesteix (Briefings Bioinform., 2021)

Improved Outcome Prediction Across Data Sources Through Robust Parameter Tuning. - Nicole Ellenbach; Anne-Laure Boulesteix; Bernd Bischl; Kristian Unger; Roman Hornung (J. Classif., 2021)

Benchmark study of feature selection strategies for multi-omics data. - Yingxia Li; Ulrich Mansmann; Shangming Du; Roman Hornung (BMC Bioinform., 2022)

Sequential Permutation Testing of Random Forest Variable Importance Measures. - Alexander Hapfelmeier; Roman Hornung; Bernhard Haller (CoRR, 2022)

Interaction forests: Identifying and exploiting interpretable quantitative and qualitative interaction effects. - Roman Hornung; Anne-Laure Boulesteix (Comput. Stat. Data Anal., 2022)

Diversity Forests: Using Split Sampling to Enable Innovative Complex Split Procedures in Random Forests. - Roman Hornung (SN Comput. Sci., 2022)

Prediction approaches for partly missing multi-omics covariate data: A literature review and an empirical comparison study. - Roman Hornung; Frederik Ludwigs; Jonas Hagenberg; Anne-Laure Boulesteix (CoRR, 2023)

Evaluating machine learning models in non-standard settings: An overview and new findings. - Roman Hornung; Malte Nalenz; Lennart Schneider; Andreas Bender 001; Ludwig Bothmann; Bernd Bischl; Thomas Augustin 001; Anne-Laure Boulesteix (CoRR, 2023)

Efficient permutation testing of variable importance measures by the example of random forests. - Alexander Hapfelmeier; Roman Hornung; Bernhard Haller (Comput. Stat. Data Anal., 2023)

Multi forests: Variable importance for multi-class outcomes. - Roman Hornung; Alexander Hapfelmeier (CoRR, 2024)

Constructing Confidence Intervals for 'the' Generalization Error - a Comprehensive Benchmark Study. - Hannah Schulz-Kümpel; Sebastian Fischer; Thomas Nagler; Anne-Laure Boulesteix; Bernd Bischl; Roman Hornung (CoRR, 2024)

Does combining numerous data types in multi-omics data improve or hinder performance in survival prediction? Insights from a large-scale benchmark study. - Yingxia Li; Tobias Herold; Ulrich Mansmann; Roman Hornung (BMC Medical Informatics Decis. Mak., 2024)