This paper is in the following e-collection/theme issue:

Cardiac Surgery (14) Clinical Information and Decision Making (1434) Decision Support for Health Professionals (1210) Machine Learning (1501) Cardiology (164)

Published on in Vol 7 (2023)

This is a member publication of University of Toronto

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/47262, first published .
Evaluation of Machine Learning Approaches for Predicting Warfarin Discharge Dose in Cardiac Surgery Patients: Retrospective Algorithm Development and Validation Study

Evaluation of Machine Learning Approaches for Predicting Warfarin Discharge Dose in Cardiac Surgery Patients: Retrospective Algorithm Development and Validation Study

Evaluation of Machine Learning Approaches for Predicting Warfarin Discharge Dose in Cardiac Surgery Patients: Retrospective Algorithm Development and Validation Study

Authors of this article:

Lindsay Dryden1 Author Orcid Image ;   Jacquelin Song1 Author Orcid Image ;   Teresa J Valenzano1 Author Orcid Image ;   Zhen Yang1 Author Orcid Image ;   Meggie Debnath1 Author Orcid Image ;   Rebecca Lin1 Author Orcid Image ;   Jane Topolovec-Vranic1 Author Orcid Image ;   Muhammad Mamdani1 Author Orcid Image ;   Tony Antoniou1 Author Orcid Image
Article Authors Cited by (1) Tweetations (5) Metrics

Lindsay Dryden   1 , BSc, PharmD ;   Jacquelin Song   1 , MSc, RD ;   Teresa J Valenzano   1 , PhD ;   Zhen Yang   1 , MSc ;   Meggie Debnath   1 , MEng ;   Rebecca Lin   1 , MHI ;   Jane Topolovec-Vranic   1 , PhD ;   Muhammad Mamdani   1 , MA, MPH, PharmD ;   Tony Antoniou   1 , PhD

1 Unity Health Toronto, Toronto, ON, Canada

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