Machine learning‐based risk prediction of malignant arrhythmia in hospitalized patients with heart failure

AIMS: Predicting the risk of malignant arrhythmias (MA) in hospitalized patients with heart failure (HF) is challenging. Machine learning (ML) can handle a large volume of complex data more effectively than traditional statistical methods. This study explored the feasibility of ML methods for predic...

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Detalles Bibliográficos
Autores principales: Wang, Qi, Li, Bin, Chen, Kangyu, Yu, Fei, Su, Hao, Hu, Kai, Liu, Zhiquan, Wu, Guohong, Yan, Ji, Su, Guohai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Original Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8712774/
https://www.ncbi.nlm.nih.gov/pubmed/34585531
http://dx.doi.org/10.1002/ehf2.13627

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8712774/
https://www.ncbi.nlm.nih.gov/pubmed/34585531
http://dx.doi.org/10.1002/ehf2.13627

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