Cargando…
Predicting patient outcomes in psychiatric hospitals with routine data: a machine learning approach
BACKGROUND: A common problem in machine learning applications is availability of data at the point of decision making. The aim of the present study was to use routine data readily available at admission to predict aspects relevant to the organization of psychiatric hospital care. A further aim was t...
Autores principales: | Wolff, J., Gary, A., Jung, D., Normann, C., Kaier, K., Binder, H., Domschke, K., Klimke, A., Franz, M. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7006066/ https://www.ncbi.nlm.nih.gov/pubmed/32028934 http://dx.doi.org/10.1186/s12911-020-1042-2 |
Ejemplares similares
-
Predicting the risk of drug-drug interactions in psychiatric hospitals
por: Wolff, J., et al.
Publicado: (2021) -
Predicting the risk of drug–drug interactions in psychiatric hospitals: a retrospective longitudinal pharmacovigilance study
por: Wolff, Jan, et al.
Publicado: (2021) -
Forecasting admissions in psychiatric hospitals before and during Covid-19: a retrospective study with routine data
por: Wolff, J., et al.
Publicado: (2022) -
Pharmacotherapy, drug-drug interactions and potentially inappropriate medication in depressive disorders
por: Wolff, Jan, et al.
Publicado: (2021) -
Hospital costs associated with psychiatric comorbidities: a retrospective study
por: Wolff, Jan, et al.
Publicado: (2018)