| scikit-survival: A Library for Time-to-Event Analysis Built on Top of scikit-learn S Pölsterl Journal of Machine Learning Research 21 (212), 1-6, 2020 | 413 | 2020 |
| BrainTorrent: A Peer-to-Peer Environment for Decentralized Federated Learning A Guha Roy, S Siddiqui, S Pölsterl, N Navab, C Wachinger arXiv e-prints, arXiv: 1905.06731, 2019 | 384* | 2019 |
| ‘Squeeze & excite’guided few-shot segmentation of volumetric images AG Roy, S Siddiqui, S Pölsterl, N Navab, C Wachinger Medical image analysis 59, 101587, 2020 | 198 | 2020 |
| 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 | 168 | 2017 |
| Fast Training of Support Vector Machines for Survival Analysis S Pölsterl, N Navab, A Katouzian European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015 …, 2015 | 151 | 2015 |
| Odefy-from discrete to continuous models J Krumsiek, S Pölsterl, DM Wittmann, FJ Theis BMC bioinformatics 11, 1-10, 2010 | 151 | 2010 |
| 2d image registration in ct images using radial image descriptors F Graf, HP Kriegel, M Schubert, S Pölsterl, A Cavallaro Medical Image Computing and Computer-Assisted Intervention–MICCAI 2011: 14th …, 2011 | 117 | 2011 |
| Detect and correct bias in multi-site neuroimaging datasets C Wachinger, A Rieckmann, S Pölsterl, ... Medical Image Analysis 67, 101879, 2021 | 106 | 2021 |
| Survival analysis for high-dimensional, heterogeneous medical data: Exploring feature extraction as an alternative to feature selection S Pölsterl, S Conjeti, N Navab, A Katouzian Artificial intelligence in medicine 72, 1-11, 2016 | 67 | 2016 |
| An efficient training algorithm for kernel survival support vector machines S Pölsterl, N Navab, A Katouzian arXiv preprint arXiv:1611.07054, 2016 | 60 | 2016 |
| Combining 3D image and tabular data via the dynamic affine feature map transform S Pölsterl, TN Wolf, C Wachinger Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021 | 50 | 2021 |
| Method to identify optimum coronary artery disease treatment A Kamen, MK Singh, S Poelsterl, LA Ladic, D Comaniciu US Patent 11,450,431, 2022 | 49 | 2022 |
| Vox2cortex: Fast explicit reconstruction of cortical surfaces from 3d mri scans with geometric deep neural networks F Bongratz, AM Rickmann, S Pölsterl, C Wachinger Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 44 | 2022 |
| A wide and deep neural network for survival analysis from anatomical shape and tabular clinical data S Pölsterl, I Sarasua, B Gutiérrez-Becker, C Wachinger Machine Learning and Knowledge Discovery in Databases: International …, 2020 | 36 | 2020 |
| Heterogeneous ensembles for predicting survival of metastatic, castrate-resistant prostate cancer patients S Pölsterl, P Gupta, L Wang, S Conjeti, A Katouzian, N Navab F1000Research 5 (2676), 2016 | 35 | 2016 |
| Quantifying confounding bias in neuroimaging datasets with causal inference C Wachinger, BG Becker, A Rieckmann, S Pölsterl Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 32 | 2019 |
| Daft: A universal module to interweave tabular data and 3d images in cnns TN Wolf, S Pölsterl, C Wachinger, ... NeuroImage 260, 119505, 2022 | 30 | 2022 |
| Braintorrent: A peer-to-peer environment for decentralized federated learning. arXiv 2019 AG Roy, S Siddiqui, S Pölsterl, N Navab, C Wachinger arXiv preprint arXiv:1905.06731, 0 | 27 | |
| Semi-structured deep piecewise exponential models P Kopper, S Pölsterl, C Wachinger, B Bischl, A Bender, D Rügamer Survival Prediction-Algorithms, Challenges and Applications, 40-53, 2021 | 26 | 2021 |
| Local hydrological conditions and spatial connectivity shape invertebrate communities after rewetting in temporary rivers D Pineda-Morante, JM Fernández-Calero, S Pölsterl, ... Hydrobiologia 849 (6), 1511-1530, 2022 | 25 | 2022 |
Christian WachingerTechnical University of MunichVerified email at csail.mit.edu
