Can machine learning improve patient selection for cardiac resynchronization therapy?
Can machine learning improve patient selection for cardiac resynchronization therapy?
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Publisher
United States: Public Library of Science
Journal title
Language
English
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Publisher
United States: Public Library of Science
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Scope and Contents
Contents
Multiple clinical trials support the effectiveness of cardiac resynchronization therapy (CRT); however, optimal patient selection remains challenging due to substantial treatment heterogeneity among patients who meet the clinical practice guidelines.
To apply machine learning to create an algorithm that predicts CRT outcome using electronic heal...
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Full title
Can machine learning improve patient selection for cardiac resynchronization therapy?
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TN_cdi_plos_journals_2300607217
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_plos_journals_2300607217
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ISSN
1932-6203
E-ISSN
1932-6203
DOI
10.1371/journal.pone.0222397
