Cargando...
Learning temporal weights of clinical events using variable importance
BACKGROUND: Longitudinal data sources, such as electronic health records (EHRs), are very valuable for monitoring adverse drug events (ADEs). However, ADEs are heavily under-reported in EHRs. Using machine learning algorithms to automatically detect patients that should have had ADEs reported in the...
Gardado en:
| Publicado en: | BMC Med Inform Decis Mak |
|---|---|
| Main Authors: | , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado: |
BioMed Central
2016
|
| Assuntos: | |
| Acceso en liña: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4965710/ https://ncbi.nlm.nih.gov/pubmed/27459993 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12911-016-0311-6 |
| Tags: |
Engadir etiqueta
Sen Etiquetas, Sexa o primeiro en etiquetar este rexistro!
|