Search Results for author: Paul Elbers

Found 6 papers, 5 papers with code

Yet Another ICU Benchmark: A Flexible Multi-Center Framework for Clinical ML

4 code implementations8 Jun 2023 Robin van de Water, Hendrik Schmidt, Paul Elbers, Patrick Thoral, Bert Arnrich, Patrick Rockenschaub

Datasets and code are not always published, and cohort definitions, preprocessing pipelines, and training setups are difficult to reproduce.

Benchmarking Kidney Function

Out-of-Distribution Detection for Medical Applications: Guidelines for Practical Evaluation

1 code implementation30 Sep 2021 Karina Zadorozhny, Patrick Thoral, Paul Elbers, Giovanni Cinà

Detection of Out-of-Distribution (OOD) samples in real time is a crucial safety check for deployment of machine learning models in the medical field.

BIG-bench Machine Learning Out-of-Distribution Detection +2

Integrating Expert ODEs into Neural ODEs: Pharmacology and Disease Progression

1 code implementation NeurIPS 2021 Zhaozhi Qian, William R. Zame, Lucas M. Fleuren, Paul Elbers, Mihaela van der Schaar

To close this gap, we propose the latent hybridisation model (LHM) that integrates a system of expert-designed ODEs with machine-learned Neural ODEs to fully describe the dynamics of the system and to link the expert and latent variables to observable quantities.

Bayesian Modelling in Practice: Using Uncertainty to Improve Trustworthiness in Medical Applications

1 code implementation20 Jun 2019 David Ruhe, Giovanni Cinà, Michele Tonutti, Daan de Bruin, Paul Elbers

In this work we show how Bayesian modelling and the predictive uncertainty that it provides can be used to mitigate risk of misguided prediction and to detect out-of-domain examples in a medical setting.

BIG-bench Machine Learning Decision Making

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