Using Deep Learning to Identify High-Risk Patients with Heart Failure with Reduced Ejection Fraction

Background: Deep Learning (DL) has not been well-established as a method to identify high-risk patients among patients with heart failure (HF). Objectives: This study aimed to use DL models to predict hospitalizations, worsening HF events, and 30-day and 90-day readmissions in patients with heart fa...

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Detalles Bibliográficos
Autores principales: Wang, Zhibo, Chen, Xin, Tan, Xi, Yang, Lingfeng, Kannapur, Kartik, Vincent, Justin L., Kessler, Garin N., Ru, Boshu, Yang, Mei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Columbia Data Analytics, LLC 2021
Materias:
Methodology and Healthcare Policy
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8322198/
https://www.ncbi.nlm.nih.gov/pubmed/34414250
http://dx.doi.org/10.36469/jheor.2021.25753

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8322198/
https://www.ncbi.nlm.nih.gov/pubmed/34414250
http://dx.doi.org/10.36469/jheor.2021.25753

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