| Prediction of overall survival for patients with metastatic castration-resistant prostate cancer: development of a prognostic model through a crowdsourced challenge with open … J Guinney, T Wang, TD Laajala, KK Winner, JC Bare, EC Neto, SA Khan, ... The Lancet Oncology 18 (1), 132-142, 2017 | 161 | 2017 |
| A strategy for high‐dimensional multivariable analysis classifies childhood asthma phenotypes from genetic, immunological, and environmental factors N Krautenbacher, N Flach, A Böck, K Laubhahn, M Laimighofer, FJ Theis, ... Allergy 74 (7), 1364-1373, 2019 | 26 | 2019 |
| Asthma in farm children is more determined by genetic polymorphisms and in non‐farm children by environmental factors N Krautenbacher, M Kabesch, E Horak, C Braun‐Fahrländer, J Genuneit, ... Pediatric allergy and immunology 32 (2), 295-304, 2021 | 22 | 2021 |
| A DREAM challenge to build prediction models for short-term discontinuation of docetaxel in metastatic castration-resistant prostate cancer F Seyednasrollah, DC Koestler, T Wang, SR Piccolo, R Vega, R Greiner, ... JCO clinical cancer informatics 1, 1-15, 2017 | 18 | 2017 |
| Correcting classifiers for sample selection bias in two-phase case-control studies N Krautenbacher, FJ Theis, C Fuchs Computational and mathematical methods in medicine 2017, 2017 | 18 | 2017 |
| Minimization and estimation of the variance of prediction errors for cross-validation designs M Fuchs, N Krautenbacher Journal of Statistical Theory and Practice 10, 420-443, 2016 | 9 | 2016 |
| Three general concepts to improve risk prediction: good data, wisdom of the crowd, recalibration I Kondofersky, M Laimighofer, C Kurz, N Krautenbacher, JF Söllner, ... F1000Research 5, 2671, 2016 | 3 | 2016 |
| Learning on complex, biased, and big data: disease risk prediction in epidemiological studies and genomic medicine on the example of childhood asthma N Krautenbacher Technische Universität München, 2018 | 2 | 2018 |
| wisdom of the crowd, recalibration [version 1; referees: 2 I Kondofersky, M Laimighofer, C Kurz, N Krautenbacher, JF Söllner, ... Institute for Cancer, 2016 | | 2016 |
| Three general concepts to improve risk prediction: good data, wisdom of the crowd, recalibration [version 1; referees: awaiting I Kondofersky, M Laimighofer, C Kurz, N Krautenbacher, JF Söllner, ... | | 2016 |
| A variance decomposition and a Central Limit Theorem for empirical losses associated with resampling designs M Fuchs, N Krautenbacher | | 2014 |
| Efficient Computation of Unconditional Error Rate Estimators for Learning Algorithms and an Application to a Biomedical Data Set N Krautenbacher | | 2014 |
