Patrick Thoral
Orcid: 0000-0001-6140-7195
According to our database1,
Patrick Thoral
authored at least 13 papers
between 2019 and 2024.
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Bibliography
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
Determining and assessing characteristics of data element names impacting the performance of annotation using Usagi.
Int. J. Medical Informatics, October, 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
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
2020
Hide-and-Seek Privacy Challenge: Synthetic Data Generation vs. Patient Re-identification.
Proceedings of the NeurIPS 2020 Competition and Demonstration Track, 2020
2019
Transferring Clinical Prediction Models Across Hospitals and Electronic Health Record Systems.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019