The application of unsupervised deep learning in predictive models using electronic health records

BACKGROUND: The main goal of this study is to explore the use of features representing patient-level electronic health record (EHR) data, generated by the unsupervised deep learning algorithm autoencoder, in predictive modeling. Since autoencoder features are unsupervised, this paper focuses on thei...

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Detalles Bibliográficos
Autores principales: Wang, Lei, Tong, Liping, Davis, Darcy, Arnold, Tim, Esposito, Tina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7043035/
https://www.ncbi.nlm.nih.gov/pubmed/32101147
http://dx.doi.org/10.1186/s12874-020-00923-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7043035/
https://www.ncbi.nlm.nih.gov/pubmed/32101147
http://dx.doi.org/10.1186/s12874-020-00923-1

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