Machine Learning to Identify Patients at Risk of Inappropriate Dosing for Renal Risk Medications: A Critical Comment on Kaas-Hansen et al [Response to Letter]

Benjamin Skov Kaas-Hansen; Cristina Leal Rodríguez; Davide Placido; Hans-Christian Thorsen-Meyer; Anna Pors Nielsen; Nicolas Dérian; Søren Brunak; Stig Ejdrup Andersen

doi:10.2147/CLEP.S375668

Machine Learning to Identify Patients at Risk of Inappropriate Dosing for Renal Risk Medications: A Critical Comment on Kaas-Hansen et al [Response to Letter]

Benjamin Skov Kaas-Hansen, Cristina Leal Rodríguez, Davide Placido, Hans-Christian Thorsen-Meyer, Anna Pors Nielsen, Nicolas Dérian, Søren Brunak, Stig Ejdrup Andersen

Department of Intensive Care

Original language	English
Journal	Clinical Epidemiology
Volume	14
Pages (from-to)	765-766
Number of pages	2
ISSN	1179-1349
DOIs	https://doi.org/10.2147/CLEP.S375668
Publication status	Published - 2022

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Kaas-Hansen, B. S., Leal Rodríguez, C., Placido, D., Thorsen-Meyer, H.-C., Nielsen, A. P., Dérian, N., Brunak, S., & Andersen, S. E. (2022). Machine Learning to Identify Patients at Risk of Inappropriate Dosing for Renal Risk Medications: A Critical Comment on Kaas-Hansen et al [Response to Letter]. Clinical Epidemiology, 14, 765-766. https://doi.org/10.2147/CLEP.S375668

Machine Learning to Identify Patients at Risk of Inappropriate Dosing for Renal Risk Medications: A Critical Comment on Kaas-Hansen et al [Response to Letter]. / Kaas-Hansen, Benjamin Skov; Leal Rodríguez, Cristina; Placido, Davide et al.
In: Clinical Epidemiology, Vol. 14, 2022, p. 765-766.

Research output: Contribution to journal › Comment/debate › Research › peer-review

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AU - Kaas-Hansen, Benjamin Skov

AU - Leal Rodríguez, Cristina

AU - Placido, Davide

AU - Thorsen-Meyer, Hans-Christian

AU - Nielsen, Anna Pors

AU - Dérian, Nicolas

AU - Brunak, Søren

AU - Andersen, Stig Ejdrup

PY - 2022

Y1 - 2022

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Machine Learning to Identify Patients at Risk of Inappropriate Dosing for Renal Risk Medications: A Critical Comment on Kaas-Hansen et al [Response to Letter]

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