Machine Learning to Identify Patients at Risk of Inappropriate Dosing for Renal Risk Medications

Department of Drug Design and Pharmacology

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

Research output: Contribution to journal › Letter › Research › peer-review

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Houlind, Morten Baltzer
Esben Iversen
Baker Nawfal Jawad
Thomas Kallemose
Hornum, Mads

Original language	English
Journal	Clinical Epidemiology
Volume	14
Pages (from-to)	763-764
ISSN	1179-1349
DOIs	https://doi.org/10.2147/CLEP.S369602
Publication status	Published - 2022

Bibliographical note

Funding Information:
Morten Baltzer Houlind was supported by a postdoctoral fellowship from The Capital Region’s Research Foundation for Health Research, Denmark (grant-A6882).

Funding Information:
This work was performed as part of the Clinical Academic Group (ACUTE-CAG) for Recovery Capacity funded by the Greater Copenhagen Health Science Partners (GCHSP).

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