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]

Morten Baltzer Houlind,1–4 Esben Iversen,1 Baker Nawfal Jawad,1 Thomas Kallemose,1 Mads Hornum5,6 1Department of Clinical Research, Copenhagen University Hospital – Amager and Hvidovre, Hvidovre, Denmark; 2The Capital Region Pharmacy, Herlev, Denmark; 3Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark; 4Emergency Department, Copenhagen University Hospital – Amager & Hvidovre, Hvidovre, Denmark; 5Department of Nephrology, Copenhagen University Hospital – Rigshospitalet, Copenhagen, Denmark; 6Department of Clinical Medicine, University of Copenhagen, Copenhagen, DenmarkCorrespondence: Morten Baltzer Houlind, Tel +45 28838563, Email morten.baltzer.houlind@regionh.dk View the original paper by Dr Kaas-Hansen and colleagues A Response to Letter has been published for this article