Matthias Hüser
Matthias Hüser
Biomedical Informatics Group, ETH Zurich
Verified email at - Homepage
Cited by
Cited by
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
SOM-VAE: Interpretable Discrete Representation Learning on Time Series
V Fortuin, M Hüser, F Locatello, H Strathmann, G Rätsch
ICLR 2019, 2018
Improving clinical predictions through unsupervised time series representation learning
X Lyu, M Hüser, SL Hyland, G Zerveas, G Rätsch
Machine Learning for Health (ML4H) Workshop at NeurIPS 2018. arXiv:1812.00490, 2018
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
Forecasting intracranial hypertension using time series and waveform features
M Hüser
MSc. thesis, ETH Zurich, 2015
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
Forecasting intracranial hypertension using multi-scale waveform metrics
M Hüser, A Kündig, W Karlen, V De Luca, M Jaggi
Physiological Measurement 41 (1), 014001, 2020
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
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
DPSOM: Deep Probabilistic Clustering with Self-Organizing Maps
L Manduchi, M Hüser, G Rätsch, V Fortuin
arXiv preprint arXiv:1910.01590, 2019
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