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Clinical Epidemiology Volume 14, 2022 - Issue
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Original Research

Using Machine Learning to Identify Patients at High Risk of Inappropriate Drug Dosing in Periods with Renal Dysfunction

Benjamin Skov Kaas-Hansen1 Clinical Pharmacology Unit, Zealand University Hospital, Roskilde, Denmark;2 NNF Center for Protein Research, University of Copenhagen, Copenhagen, Denmark;3 Section for Biostatistics, Department of Public Health, University of Copenhagen, Copenhagen, DenmarkCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0003-1023-0371View further author information
ORCID Icon,
Cristina Leal Rodríguez2 NNF Center for Protein Research, University of Copenhagen, Copenhagen, DenmarkORCID Iconhttps://orcid.org/0000-0002-3133-0630View further author information
ORCID Icon,
Davide Placido2 NNF Center for Protein Research, University of Copenhagen, Copenhagen, DenmarkORCID Iconhttps://orcid.org/0000-0002-8327-8838View further author information
ORCID Icon,
Hans-Christian Thorsen-Meyer2 NNF Center for Protein Research, University of Copenhagen, Copenhagen, Denmark;4 Department of Intensive Care Medicine, Copenhagen University Hospital (Rigshospitalet), Copenhagen, DenmarkORCID Iconhttps://orcid.org/0000-0001-7002-3089View further author information
ORCID Icon,
Anna Pors Nielsen2 NNF Center for Protein Research, University of Copenhagen, Copenhagen, DenmarkORCID Iconhttps://orcid.org/0000-0001-7903-5051View further author information
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Nicolas Dérian5 Data and Development Support, Region Zealand, Sorø, DenmarkView further author information
,
Søren Brunak2 NNF Center for Protein Research, University of Copenhagen, Copenhagen, DenmarkView further author information
&
Stig Ejdrup Andersen1 Clinical Pharmacology Unit, Zealand University Hospital, Roskilde, DenmarkView further author information
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Pages 213-223 | Published online: 22 Feb 2022

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Benjamin Skov Kaas-Hansen, Cristina Leal Rodríguez, Davide Placido, Hans-Christian Thorsen-Meyer, Anna Pors Nielsen, Nicolas Dérian, Søren Brunak & Stig Ejdrup Andersen. (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, pages 765-766.
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Morten Baltzer Houlind, Esben Iversen, Baker Nawfal Jawad, Thomas Kallemose & Mads Hornum. (2022) Machine Learning to Identify Patients at Risk of Inappropriate Dosing for Renal Risk Medications: A Critical Comment on Kaas-Hansen et al [Letter]. Clinical Epidemiology 14, pages 763-764.
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Articles from other publishers (1)

Supatcha Sassanarakkit, Sudarat Hadpech & Visith Thongboonkerd. (2023) Theranostic roles of machine learning in clinical management of kidney stone disease. Computational and Structural Biotechnology Journal 21, pages 260-266.
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