Patrick Thoral

Orcid: 0000-0001-6140-7195

According to our database1, Patrick Thoral authored at least 12 papers between 2019 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

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

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


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