Machine learning-based risk model using (123)I-metaiodobenzylguanidine to differentially predict modes of cardiac death in heart failure

BACKGROUND: Cardiac sympathetic dysfunction is closely associated with cardiac mortality in patients with chronic heart failure (CHF). We analyzed the ability of machine learning incorporating (123)I-metaiodobenzylguanidine (MIBG) to differentially predict risk of life-threatening arrhythmic events...

Descripción completa

Detalles Bibliográficos
Autores principales: Nakajima, Kenichi, Nakata, Tomoaki, Doi, Takahiro, Tada, Hayato, Maruyama, Koji
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2020
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8873155/
https://www.ncbi.nlm.nih.gov/pubmed/32410060
http://dx.doi.org/10.1007/s12350-020-02173-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8873155/
https://www.ncbi.nlm.nih.gov/pubmed/32410060
http://dx.doi.org/10.1007/s12350-020-02173-6

Ejemplares similares