| Early prediction of circulatory failure in the intensive care unit using machine learning SL Hyland, M Faltys, M Hüser, X Lyu, T Gumbsch, C Esteban, C Bock, ... Nature Medicine 26 (3), 364-373, 2020 | 200 | 2020 |
| Topological Autoencoders M Moor, M Horn, B Rieck, K Borgwardt International Conference on Machine Learning (ICML), 7045--7054, 2020 | 110 | 2020 |
| Accelerating detection of lung pathologies with explainable ultrasound image analysis J Born, N Wiedemann, M Cossio, C Buhre, G Brändle, K Leidermann, ... Applied Sciences 11 (2), 672, 2021 | 101 | 2021 |
| Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology B Rieck, M Togninalli, C Bock, M Moor, M Horn, T Gumbsch, K Borgwardt International Conference on Learning Representations (ICLR), 2019., 2018 | 99 | 2018 |
| Early Recognition of Sepsis with Gaussian Process Temporal Convolutional Networks and Dynamic Time Warping M Moor, M Horn, B Rieck, D Roqueiro, K Borgwardt Proceedings of the 4th Machine Learning for Healthcare Conference, 2019., 2019 | 78* | 2019 |
| A survey of topological machine learning methods F Hensel, M Moor, B Rieck Frontiers in Artificial Intelligence 4, 681108, 2021 | 74 | 2021 |
| Set Functions for Time Series M Horn, M Moor, C Bock, B Rieck, K Borgwardt International Conference on Machine Learning (ICML), 4353-4363, 2020 | 70 | 2020 |
| Early prediction of sepsis in the ICU using machine learning: a systematic review M Moor, B Rieck, M Horn, CR Jutzeler, K Borgwardt Frontiers in medicine 8, 348, 2021 | 67 | 2021 |
| Topological Graph Neural Networks M Horn, E De Brouwer, M Moor, Y Moreau, B Rieck, K Borgwardt International Conference on Learning Representations (ICLR), 2022, 2022 | 33 | 2022 |
| Association mapping in biomedical time series via statistically significant shapelet mining C Bock, T Gumbsch, M Moor, B Rieck, D Roqueiro, K Borgwardt Bioinformatics 34 (13), i438-i446, 2018 | 27 | 2018 |
| Foundation models for generalist medical artificial intelligence M Moor, O Banerjee, ZSH Abad, HM Krumholz, J Leskovec, EJ Topol, ... Nature 616 (7956), 259-265, 2023 | 18 | 2023 |
| Machine Learning for Biomedical Time Series Classification: From Shapelets to Deep Learning C Bock, M Moor, CR Jutzeler, K Borgwardt Artificial Neural Networks, 33-71, 2020 | 15 | 2020 |
| Quantification of liver, subcutaneous, and visceral adipose tissues by MRI before and after bariatric surgery AC Meyer-Gerspach, R Peterli, M Moor, P Madörin, A Schötzau, D Nabers, ... Obesity surgery 29, 2795-2805, 2019 | 15 | 2019 |
| Path Imputation Strategies for Signature Models M Moor, M Horn, C Bock, K Borgwardt, B Rieck ICML 2020 Workshop on the Art of Learning with Missing Values (Artemiss), 2020 | 6 | 2020 |
| Path Imputation Strategies for Signature Models of Irregular Time Series M Moor, M Horn, C Bock, K Borgwardt, B Rieck arXiv preprint arXiv:2005.12359, 2020 | 6* | 2020 |
| Predicting sepsis in multi-site, multi-national intensive care cohorts using deep learning M Moor, N Bennet, D Plecko, M Horn, B Rieck, N Meinshausen, ... arXiv preprint arXiv:2107.05230, 2021 | 4 | 2021 |
| Enhancing statistical power in temporal biomarker discovery through representative shapelet mining T Gumbsch, C Bock, M Moor, B Rieck, K Borgwardt Bioinformatics 36 (Supplement_2), i840-i848, 2020 | 4 | 2020 |
| Challenging Euclidean Topological Autoencoders M Moor, M Horn, K Borgwardt, B Rieck Topological Data Analysis and Beyond Workshop at NeurIPS 2020, 2020 | 3 | 2020 |
| Prediction of recovery from multiple organ dysfunction syndrome in pediatric sepsis patients B Fan, J Klatt, MM Moor, LA Daniels, LN Sanchez-Pinto, PKA Agyeman, ... Bioinformatics 38 (Supplement_1), i101-i108, 2022 | 2 | 2022 |
| Learning Individualized Treatment Rules with Estimated Translated Inverse Propensity Score Z Wu, Y Yang, Y Ma, Y Liu, R Zhao, M Moor, V Tresp 2020 IEEE International Conference on Healthcare Informatics (ICHI), 1-11, 2020 | 2 | 2020 |
Bastian RieckAIDOS Lab, Institute of AI for Health, Helmholtz Zentrum MünchenVerified email at helmholtz-muenchen.de
