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,1-3 Cristina Leal Rodríguez,2 Davide Placido,2 Hans-Christian Thorsen-Meyer,2,4 Anna Pors Nielsen,2 Nicolas Dérian,5 Søren Brunak,2 Stig Ejdrup Andersen1 1Clinical Pharmacology Unit, Zealand University Hospital, Roskilde, Denmark; 2NNF Center for Protein Research, University of Copenhagen, Copenhagen, Denmark; 3Section for Biostatistics, Department of Public Health, University of Copenhagen, Copenhagen, Denmark; 4Department of Intensive Care Medicine, Copenhagen University Hospital (Rigshospitalet), Copenhagen, Denmark; 5Data and Development Support, Region Zealand, DenmarkCorrespondence: Benjamin Skov Kaas-Hansen, Department of Intensive Care, Copenhagen University Hospital - Rigshospitalet, Blegdamsvej 9, Copenhagen, 2100, Denmark, Tel +45 60 19 68 01, Email epiben@hey.com View the original paper by Dr Kaas-Hansen and colleagues This is in response to the Letter to the Editor