Systematic review of machine learning models for personalised dosing of heparin.

Journal: British journal of clinical pharmacology
PMID: 33835524

Abstract

AIM: To identify and critically appraise studies of prediction models, developed using machine learning (ML) methods, for determining the optimal dosing of unfractionated heparin (UFH).

Authors

  • Nazanin Falconer
    Department of Pharmacy, Princess Alexandra Hospital, Brisbane, Queensland, 4102, Australia.
  • Ahmad Abdel-Hafez
    Clinical Informatics, Princess Alexandra Hospital, Brisbane, Queensland, 4102, Australia.
  • Ian A Scott
    University of Queensland, Brisbane, Queensland, Australia (I.A.S.).
  • Sven Marxen
    Department of Pharmacy, Logan and Beaudesert Hospitals, Meadowbrook, Metro South Health, Brisbane, QLD, 4131, Australia.
  • Stephen Canaris
    Clinical Informatics, Princess Alexandra Hospital, Brisbane, Queensland, 4102, Australia.
  • Michael Barras
    Department of Pharmacy, Princess Alexandra Hospital, Brisbane, Queensland, 4102, Australia.

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