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32 results on '"Urlings-Strop, Louise C."'

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1. A pragmatic approach to estimating average treatment effects from EHR data: the effect of prone positioning on mechanically ventilated COVID-19 patients

2. 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

3. Predicting responders to prone positioning in mechanically ventilated patients with COVID-19 using machine learning

4. Predictors for extubation failure in COVID-19 patients using a machine learning approach

5. The Dutch Data Warehouse, a multicenter and full-admission electronic health records database for critically ill COVID-19 patients

6. Some Patients Are More Equal Than Others: Variation in Ventilator Settings for Coronavirus Disease 2019 Acute Respiratory Distress Syndrome

7. The Relationship between Extracurricular Activities Assessed during Selection and during Medical School and Performance

8. Incidence, Risk Factors and Outcome of Suspected Central Venous Catheter-related Infections in Critically Ill COVID-19 Patients

9. Delirium in older COVID‐19 patients: Evaluating risk factors and outcomes

10. Large-scale ICU data sharing for global collaboration: the first 1633 critically ill COVID-19 patients in the Dutch Data Warehouse

11. Delirium in older COVID-19 patients:Evaluating risk factors and outcomes

12. 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

13. Rapid Evaluation of Coronavirus Illness Severity (RECOILS) in intensive care:Development and validation of a prognostic tool for in-hospital mortality

14. Incidence, Risk Factors and Outcome of Suspected Central Venous Catheter-related Infections in Critically Ill COVID-19 Patients: A Multicenter Retrospective Cohort Study

15. Rapid evaluation of Coronavirus Illness Severity (RECOILS) in intensive care: Development and validation of a prognostic tool for in-hospital mortality

16. Evolution of Clinical Phenotypes of COVID-19 Patients During Intensive Care Treatment: An Unsupervised Machine Learning Analysis

17. Additional file 1 of Predicting responders to prone positioning in mechanically ventilated patients with COVID-19 using machine learning

18. Risk factors for adverse outcomes during mechanical ventilation of 1152 COVID-19 patients: a multicenter machine learning study with highly granular data from the Dutch Data Warehouse

19. Rapid Evaluation of Coronavirus Illness Severity (RECOILS) in intensive care: Development and validation of a prognostic tool for in‐hospital mortality

20. Additional file 1 of Risk factors for adverse outcomes during mechanical ventilation of 1152 COVID-19 patients: a multicenter machine learning study with highly granular data from the Dutch Data Warehouse

21. Additional file 3 of The Dutch Data Warehouse, a multicenter and full-admission electronic health records database for critically ill COVID-19 patients

22. Additional file 1 of Predictors for extubation failure in COVID-19 patients using a machine learning approach

23. Additional file 2 of The Dutch Data Warehouse, a multicenter and full-admission electronic health records database for critically ill COVID-19 patients

24. Some Patients Are More Equal Than Others: Variation in Ventilator Settings for Coronavirus Disease 2019 Acute Respiratory Distress Syndrome

25. Risk factors for adverse outcomes during mechanical ventilation of 1152 COVID-19 patients:a multicenter machine learning study with highly granular data from the Dutch Data Warehouse

26. Some Patients Are More Equal Than Others:Variation in Ventilator Settings for Coronavirus Disease 2019 Acute Respiratory Distress Syndrome

32. Rapid Evaluation of Coronavirus Illness Severity (RECOILS) in intensive care: Development and validation of a prognostic tool for in-hospital mortality.

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