Recurrent disease progression networks for modelling risk trajectory of heart failure

MOTIVATION: Recurrent neural networks (RNN) are powerful frameworks to model medical time series records. Recent studies showed improved accuracy of predicting future medical events (e.g., readmission, mortality) by leveraging large amount of high-dimensional data. However, very few studies have exp...

Descripción completa

Detalles Bibliográficos
Autores principales: Lu, Xing Han, Liu, Aihua, Fuh, Shih-Chieh, Lian, Yi, Guo, Liming, Yang, Yi, Marelli, Ariane, Li, Yue
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7787457/
https://www.ncbi.nlm.nih.gov/pubmed/33406155
http://dx.doi.org/10.1371/journal.pone.0245177

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7787457/
https://www.ncbi.nlm.nih.gov/pubmed/33406155
http://dx.doi.org/10.1371/journal.pone.0245177

Ejemplares similares