Paul W. G. Elbers
Orcid: 0000-0003-0447-6893
According to our database1,
Paul W. G. Elbers
authored at least 25 papers
between 2011 and 2024.
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Bibliography
2024
Guideline-informed reinforcement learning for mechanical ventilation in critical care.
Artif. Intell. Medicine, January, 2024
Comparative performance of intensive care mortality prediction models based on manually curated versus automatically extracted electronic health record data.
Int. J. Medical Informatics, 2024
Proceedings of the Twelfth International Conference on Learning Representations, 2024
2023
Augmented intelligence facilitates concept mapping across different electronic health records.
Int. J. Medical Informatics, November, 2023
Prognostic models of in-hospital mortality of intensive care patients using neural representation of unstructured text: A systematic review and critical appraisal.
J. Biomed. Informatics, October, 2023
Determining and assessing characteristics of data element names impacting the performance of annotation using Usagi.
Int. J. Medical Informatics, October, 2023
Assessing the FAIRness of databases on the EHDEN portal: A case study on two Dutch ICU databases.
Int. J. Medical Informatics, August, 2023
Generalizable calibrated machine learning models for real-time atrial fibrillation risk prediction in ICU patients.
Int. J. Medical Informatics, July, 2023
Proceedings of the Advances and Trends in Artificial Intelligence. Theory and Applications, 2023
2022
Assess and validate predictive performance of models for in-hospital mortality in COVID-19 patients: A retrospective cohort study in the Netherlands comparing the value of registry data with high-granular electronic health records.
Int. J. Medical Informatics, 2022
Can we reliably automate clinical prognostic modelling? A retrospective cohort study for ICU triage prediction of in-hospital mortality of COVID-19 patients in the Netherlands.
Int. J. Medical Informatics, 2022
Improving adaptability to new environments and removing catastrophic forgetting in Reinforcement Learning by using an eco-system of agents.
CoRR, 2022
Improving generalization to new environments and removing catastrophic forgetting in Reinforcement Learning by using an eco-system of agents.
Proceedings of the IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, 2022
Prediction of Acute Kidney Injury in the Intensive Care Unit: Preliminary Findings in a European Open Access Database.
Proceedings of the Challenges of Trustable AI and Added-Value on Health, 2022
Predicting readmission or death after discharge from the ICU: External validation and retraining of a machine learning model.
Proceedings of the AMIA 2022, 2022
2021
Out-of-Distribution Detection for Medical Applications: Guidelines for Practical Evaluation.
CoRR, 2021
A pragmatic approach to estimating average treatment effects from EHR data: the effect of prone positioning on mechanically ventilated COVID-19 patients.
CoRR, 2021
Transatlantic transferability of a new reinforcement learning model for optimizing haemodynamic treatment for critically ill patients with sepsis.
Artif. Intell. Medicine, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
2020
Hide-and-Seek Privacy Challenge: Synthetic Data Generation vs. Patient Re-identification.
Proceedings of the NeurIPS 2020 Competition and Demonstration Track, 2020
2019
Bayesian Modelling in Practice: Using Uncertainty to Improve Trustworthiness in Medical Applications.
CoRR, 2019
Transferring Clinical Prediction Models Across Hospitals and Electronic Health Record Systems.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019
2012
Erratum to: Rapid automatic assessment of microvascular density in sidestream dark field images.
Medical Biol. Eng. Comput., 2012
2011
Medical Biol. Eng. Comput., 2011