From Single-Hospital to Multi-Centre Applications: Enhancing the
Generalisability of Deep Learning Models for Adverse Event Prediction in the
ICU

v1v2 (latest)

From Single-Hospital to Multi-Centre Applications: Enhancing the Generalisability of Deep Learning Models for Adverse Event Prediction in the ICU

27 March 2023

Patrick Rockenschaub

ArXiv (abs)PDF HTML

Papers citing "From Single-Hospital to Multi-Centre Applications: Enhancing the Generalisability of Deep Learning Models for Adverse Event Prediction in the ICU"

8 / 8 papers shown

Title
Evaluation of Active Feature Acquisition Methods for Time-varying Feature Settings Henrik von Kleist Alireza Zamanian I. Shpitser Narges Ahmidi OffRL 187 3 0 03 Dec 2023
HiRID-ICU-Benchmark -- A Comprehensive Machine Learning Benchmark on High-resolution ICU Data Hugo Yèche Rita Kuznetsova M. Zimmermann Matthias Huser Xinrui Lyu M. Faltys Gunnar Rätsch 114 42 0 16 Nov 2021
Predicting sepsis in multi-site, multi-national intensive care cohorts using deep learning Michael Moor Nicolas Bennet Drago Plečko Max Horn Bastian Rieck N. Meinshausen Peter Buhlmann Karsten Borgwardt 48 6 0 12 Jul 2021
In Search of Lost Domain Generalization Ishaan Gulrajani David Lopez-Paz OOD 103 1,157 0 02 Jul 2020
Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization Shiori Sagawa Pang Wei Koh Tatsunori B. Hashimoto Percy Liang OOD 108 1,249 0 20 Nov 2019
Learning to Generalize: Meta-Learning for Domain Generalization Da Li Yongxin Yang Yi-Zhe Song Timothy M. Hospedales OOD 102 1,430 0 10 Oct 2017
Deep CORAL: Correlation Alignment for Deep Domain Adaptation Baochen Sun Kate Saenko OOD 105 3,170 0 06 Jul 2016
On the Properties of Neural Machine Translation: Encoder-Decoder Approaches Kyunghyun Cho B. V. Merrienboer Dzmitry Bahdanau Yoshua Bengio AI4CE AIMat 265 6,791 0 03 Sep 2014

We use cookies and other tracking technologies to improve your browsing experience on our website, to show you personalized content and targeted ads, to analyze our website traffic, and to understand where our visitors are coming from. See our policy.