Ensembles of randomized trees using diverse distributed representations of clinical events

BACKGROUND: Learning deep representations of clinical events based on their distributions in electronic health records has been shown to allow for subsequent training of higher-performing predictive models compared to the use of shallow, count-based representations. The predictive performance may be...

Descripción completa

Detalles Bibliográficos
Autores principales: Henriksson, Aron, Zhao, Jing, Dalianis, Hercules, Boström, Henrik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4965720/
https://www.ncbi.nlm.nih.gov/pubmed/27459846
http://dx.doi.org/10.1186/s12911-016-0309-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4965720/
https://www.ncbi.nlm.nih.gov/pubmed/27459846
http://dx.doi.org/10.1186/s12911-016-0309-0

Ejemplares similares