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Can machine learning improve patient selection for cardiac resynchronization therapy?
RATIONALE: 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. OBJECTIVE: To apply machine learning t...
Autores principales: | Hu, Szu-Yeu, Santus, Enrico, Forsyth, Alexander W., Malhotra, Devvrat, Haimson, Josh, Chatterjee, Neal A., Kramer, Daniel B., Barzilay, Regina, Tulsky, James A., Lindvall, Charlotta |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6776390/ https://www.ncbi.nlm.nih.gov/pubmed/31581234 http://dx.doi.org/10.1371/journal.pone.0222397 |
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