Echocardiographic phenogrouping by machine learning for risk stratification in the general population

AIMS : There is a need for better phenotypic characterization of the asymptomatic stages of cardiac maladaptation. We tested the hypothesis that an unsupervised clustering analysis utilizing echocardiographic indexes reflecting left heart structure and function could identify phenotypically distinct...

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Detalles Bibliográficos
Autores principales: Sabovčik, František, Cauwenberghs, Nicholas, Vens, Celine, Kuznetsova, Tatiana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Original Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9707985/
https://www.ncbi.nlm.nih.gov/pubmed/36713600
http://dx.doi.org/10.1093/ehjdh/ztab042

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9707985/
https://www.ncbi.nlm.nih.gov/pubmed/36713600
http://dx.doi.org/10.1093/ehjdh/ztab042

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