Matthias Hüser

According to our database, Matthias Hüser authored at least 14 papers between 2018 and 2021.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2021

Machine Learning Approaches for Patient Monitoring in the Intensive Care Unit.

Matthias Hüser

PhD thesis, 2021

Early prediction of respiratory failure in the intensive care unit.

Matthias Hüser, Martin Faltys, Xinrui Lyu, Chris Barber, Stephanie L. Hyland, Tobias M. Merz, Gunnar Rätsch

CoRR, 2021

WRSE - a non-parametric weighted-resolution ensemble for predicting individual survival distributions in the ICU.

Jonathan Heitz, Joanna Ficek, Martin Faltys, Tobias M. Merz, Gunnar Rätsch, Matthias Hüser

Proceedings of AAAI Symposium on Survival Prediction, 2021

HiRID-ICU-Benchmark - A Comprehensive Machine Learning Benchmark on High-resolution ICU Data.

Hugo Yèche, Rita Kuznetsova, Marc Zimmermann, Matthias Hüser, Xinrui Lyu, Martin Faltys, Gunnar Rätsch

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Neighborhood Contrastive Learning Applied to Online Patient Monitoring.

Hugo Yèche, Gideon Dresdner, Francesco Locatello, Matthias Hüser, Gunnar Rätsch

Proceedings of the 38th International Conference on Machine Learning, 2021

T-DPSOM: an interpretable clustering method for unsupervised learning of patient health states.

Laura Manduchi, Matthias Hüser, Martin Faltys, Julia E. Vogt, Gunnar Rätsch, Vincent Fortuin

Proceedings of the ACM CHIL '21: ACM Conference on Health, 2021

2019

Variational PSOM: Deep Probabilistic Clustering with Self-Organizing Maps.

Laura Manduchi, Matthias Hüser, Gunnar Rätsch, Vincent Fortuin

CoRR, 2019

Machine learning for early prediction of circulatory failure in the intensive care unit.

Stephanie L. Hyland, Martin Faltys, Matthias Hüser, Xinrui Lyu, Thomas Gumbsch, Cristóbal Esteban, Christian Bock, Max Horn, Michael Moor, Bastian Rieck, Marc Zimmermann, Dean A. Bodenham, Karsten M. Borgwardt, Gunnar Rätsch, Tobias M. Merz

CoRR, 2019

Forecasting intracranial hypertension using multi-scale waveform metrics.

Matthias Hüser, Adrian Kündig, Walter Karlen, Valeria De Luca, Martin Jaggi

CoRR, 2019

SOM-VAE: Interpretable Discrete Representation Learning on Time Series.

Vincent Fortuin, Matthias Hüser, Francesco Locatello, Heiko Strathmann, Gunnar Rätsch

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Improving Clinical Predictions through Unsupervised Time Series Representation Learning.

Xinrui Lyu, Matthias Hüser, Stephanie L. Hyland, George Zerveas, Gunnar Rätsch

CoRR, 2018

Deep Self-Organization: Interpretable Discrete Representation Learning on Time Series.

Vincent Fortuin, Matthias Hüser, Francesco Locatello, Heiko Strathmann, Gunnar Rätsch

CoRR, 2018

Predicting circulatory system deterioration in intensive care unit patients.

Stephanie L. Hyland, Matthias Hüser, Xinrui Lyu, Martin Faltys, Tobias Merz, Gunnar Rätsch

Proceedings of the First Joint Workshop on AI in Health organized as part of the Federated AI Meeting (FAIM 2018), 2018

A Machine Learning-based Early Warning System for Circulatory System Deterioration in Intensive Care Unit Patients.

Stephanie L. Hyland, Martin Faltys, Matthias Hüser, Xinrui Lyu, Cristóbal Esteban, Gunnar Rätsch, Tobias Merz

Proceedings of the AMIA 2018, 2018