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5 results on '"Beerbaum Philipp"'

1. Additional file 1 of Le Cœur en Sabot: shape associations with adverse events in repaired tetralogy of Fallot

Author

Mîra, Anna, Lamata, Pablo, Pushparajah, Kuberan, Abraham, Georgina, Mauger, Charlène A., McCulloch, Andrew D., Omens, Jeffrey H., Bissell, Malenka M., Blair, Zach, Huffaker, Tyler, Tandon, Animesh, Engelhardt, Sandy, Koehler, Sven, Pickardt, Thomas, Beerbaum, Philipp, Sarikouch, Samir, Latus, Heiner, Greil, Gerald, Young, Alistair A., and Hussain, Tarique

Abstract

Additional file 1. Additional data.

Published
2022
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2. Additional file 2 of Le Cœur en Sabot: shape associations with adverse events in repaired tetralogy of Fallot

Author

Mîra, Anna, Lamata, Pablo, Pushparajah, Kuberan, Abraham, Georgina, Mauger, Charlène A., McCulloch, Andrew D., Omens, Jeffrey H., Bissell, Malenka M., Blair, Zach, Huffaker, Tyler, Tandon, Animesh, Engelhardt, Sandy, Koehler, Sven, Pickardt, Thomas, Beerbaum, Philipp, Sarikouch, Samir, Latus, Heiner, Greil, Gerald, Young, Alistair A., and Hussain, Tarique

Abstract

Additional file 2: Video S1. Animations of shape variations associated with adverse outcomes.

Published
2022
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3. Additional file 1 of Clinical evaluation of an interoperable clinical decision-support system for the detection of systemic inflammatory response syndrome in critically ill children

Author

Wulff, Antje, Montag, Sara, Rübsamen, Nicole, Dziuba, Friederike, Marschollek, Michael, Beerbaum, Philipp, Karch, André, and Jack, Thomas

Abstract

Additional file 1: Appendix 1. STARD checklist. Appendix 2. Details of changes to published study protocol. Appendix 3. Routine data used from patient data management system for CDSS assessment of all participants. Appendix 4. Strategy for SIRS episode evaluation with examples. Appendix 5. Flow diagram for recruited patients with intensive care days and patient’s PICU stays. Appendix 6. Submitted forms during routine assessment per shift and per day. Appendix 7. False decisions from the CDSS diagnostic approach, classified into error categories.

Published
2021
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5. Additional file 1: of Development and validation of a diagnostic model for early differentiation of sepsis and non-infectious SIRS in critically ill children - a data-driven approach using machine-learning algorithms

Author

Lamping, Florian, Jack, Thomas, Rübsamen, Nicole, Sasse, Michael, Beerbaum, Philipp, Mikolajczyk, Rafael, Boehne, Martin, and Karch, André

Abstract

Table S1: Overview of all sepsis cases with site of infection and relevant corresponding infectiological data. Table S2: Systematic Overview of the Predictors used in the Analysis. Table S3: Overview of all models in the backward selection procedure. Methods S1: Detailed description and explanation of data analysis approach. Code S1: R code for the main analysis. Figure S1: AUCs of the time-split approach with different mtry parameter. Figure S2: ROC analysis without validation procedure (“Apparent Performance”). (DOCX 81 kb)

Published
2018
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