Matthias Hüser
Matthias Hüser
AI4Life Residency Program, Novartis Institutes for Biomedical Research (NIBR)
Bestätigte E-Mail-Adresse bei novartis.com - Startseite
Titel
Zitiert von
Zitiert von
Jahr
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
3102018
SOM-VAE: Interpretable Discrete Representation Learning on Time Series
V Fortuin, M Hüser, F Locatello, H Strathmann, G Rätsch
ICLR 2019, 2018
672018
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
572020
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
202018
DPSOM: Deep Probabilistic Clustering with Self-Organizing Maps
L Manduchi, M Hüser, G Rätsch, V Fortuin
arXiv preprint arXiv:1910.01590, 2019
92019
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
62020
Forecasting intracranial hypertension using time series and waveform features
M Hüser
MSc. thesis, ETH Zurich, 2015
42015
Deep Self-Organization: Interpretable Discrete Representation Learning on Time Series (2018)
V Fortuin, M Hüser, F Locatello, H Strathmann, G Rätsch
arXiv preprint arXiv:1806.02199, 1806
41806
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
32015
T-DPSOM: an interpretable clustering method for unsupervised learning of patient health states
L Manduchi, M Hüser, M Faltys, J Vogt, G Rätsch, V Fortuin
Proceedings of the Conference on Health, Inference, and Learning, 236-245, 2021
22021
Neighborhood Contrastive Learning Applied to Online Patient Monitoring
H Yèche, G Dresdner, F Locatello, M Hüser, G Rätsch
arXiv preprint arXiv:2106.05142, 2021
12021
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
12016
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
1*
HiRID-ICU-Benchmark---A Comprehensive Machine Learning Benchmark on High-resolution ICU Data.
H Yèche, R Kuznetsova, M Zimmermann, M Hüser, X Lyu, M Faltys, ...
2021
Early prediction of respiratory failure in the intensive care unit
M Hüser, M Faltys, X Lyu, C Barber, SL Hyland, TM Merz, G Rätsch
arXiv preprint arXiv:2105.05728, 2021
2021
WRSE-a non-parametric weighted-resolution ensemble for predicting individual survival distributions in the ICU
J Heitz, J Ficek, M Faltys, TM Merz, G Rätsch, M Hüser
Survival Prediction-Algorithms, Challenges and Applications, 54-69, 2021
2021
Machine Learning Approaches for Patient Monitoring in the Intensive Care Unit
M Hüser
ETH Zurich, 2021
2021
A Machine Learning-based Early Warning System for Circulatory System Deterioration in Intensive Care Unit Patients
SL Hyland, M Faltys, M Hüser, X Lyu, C Esteban, G Rätsch, T Merz
AMIA, 2018
2018
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