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...

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Detalles Bibliográficos
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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Research Article
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

Internet

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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