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

Formative Evaluation of Digital Health Interventions (2415) Clinical Informatics (1022) Clinical Information and Decision Making (1407) Machine Learning (1465)

Published on in Vol 7 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/41725, first published .
Machine Learning and Causal Approaches to Predict Readmissions and Its Economic Consequences Among Canadian Patients With Heart Disease: Retrospective Study

Machine Learning and Causal Approaches to Predict Readmissions and Its Economic Consequences Among Canadian Patients With Heart Disease: Retrospective Study

Machine Learning and Causal Approaches to Predict Readmissions and Its Economic Consequences Among Canadian Patients With Heart Disease: Retrospective Study

Authors of this article:

Ethan Rajkumar1 Author Orcid Image ;   Kevin Nguyen2 Author Orcid Image ;   Sandra Radic2 Author Orcid Image ;   Jubelle Paa2 Author Orcid Image ;   Qiyang Geng3 Author Orcid Image
Article Authors Cited by Tweetations (2) Metrics

Ethan Rajkumar   1 ;   Kevin Nguyen   2 * ;   Sandra Radic   2 * ;   Jubelle Paa   2 * ;   Qiyang Geng   3 * , BASc

1 Department of Chemistry, Faculty of Science, The University of British Columbia, Vancouver, BC, Canada

2 Department of Computer Science, Faculty of Science, The University of British Columbia, Vancouver, BC, Canada

3 School of Biomedical Engineering, Faculty of Applied Sciences, University of British Columbia, Vancouver, BC, Canada

*these authors contributed equally

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