Identifying treatment heterogeneity in atrial fibrillation using a novel causal machine learning met...
Identifying treatment heterogeneity in atrial fibrillation using a novel causal machine learning method
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Publisher
United States: Elsevier Inc
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Language
English
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Publisher
United States: Elsevier Inc
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Scope and Contents
Contents
Lifelong oral anticoagulation is recommended in patients with atrial fibrillation (AF) to prevent stroke. Over the last decade, multiple new oral anticoagulants (OACs) have expanded the number of treatment options for these patients. While population-level effectiveness of OACs has been compared, it is unclear if there is variability in benefit and...
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Full title
Identifying treatment heterogeneity in atrial fibrillation using a novel causal machine learning method
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TN_cdi_proquest_miscellaneous_2786093885
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_2786093885
Other Identifiers
ISSN
0002-8703
E-ISSN
1097-6744
DOI
10.1016/j.ahj.2023.02.015
