| Comprehensive analysis of alternative splicing across tumors from 8,705 patients A Kahles, KV Lehmann, NC Toussaint, M Hüser, SG Stark, ... Cancer cell 34 (2), 211-224. e6, 2018 | 93 | 2018 |
| SOM-VAE: Interpretable Discrete Representation Learning on Time Series V Fortuin, M Hüser, F Locatello, H Strathmann, G Rätsch ICLR 2019, 2018 | 12 | 2018 |
| Improving clinical predictions through unsupervised time series representation learning X Lyu, M Hüser, SL Hyland, G Zerveas, G Rätsch arXiv preprint arXiv:1812.00490, 2018 | 4 | 2018 |
| Forecasting intracranial hypertension using waveform and time series features M Hüser, V De Luca, M Jaggi, W Karlen, E Keller Vasospasm, The International Conference on Neurovascular Events after …, 2015 | 3 | 2015 |
| Forecasting intracranial hypertension using time series and waveform features M Hüser MSc. thesis, ETH Zurich, 2015 | 3 | 2015 |
| Temporal prediction of cerebral hypoxia in neurointensive care patients: a feasibility study V De Luca, M Hüser, M Jaggi, W Karlen, E Keller 16th International Symposium on Intracranial Pressure and Neuromonitoring, 2016 | 1 | 2016 |
| Variational PSOM: Deep Probabilistic Clustering with Self-Organizing Maps L Manduchi, M Hüser, G Rätsch, V Fortuin arXiv preprint arXiv:1910.01590, 2019 | | 2019 |
| Machine learning for early prediction of circulatory failure in the intensive care unit SL Hyland, M Faltys, M Hüser, X Lyu, T Gumbsch, C Esteban, C Bock, ... arXiv preprint arXiv:1904.07990, 2019 | | 2019 |
| Forecasting intracranial hypertension using multi-scale waveform metrics M Hüser, A Kündig, W Karlen, V De Luca, M Jaggi arXiv preprint arXiv:1902.09499, 2019 | | 2019 |
| Predicting Circulatory System Deterioration in Intensive Care Unit Patients SL Hyland, M Faltys, M Hüser, X Lyu, C Esteban, T Merz, G Rätsch Proceedings of the 1st Joint Workshop on AI in Health, 0 | | |
Valeria De LucaData Scientist, Novartis Institutes for Biomedical ResearchVerified email at novartis.com
