Development and Validation of an Electronic Health Record–Based Machine Learning Model to Estimate Delirium Risk in Newly Hospitalized Patients Without Known Cognitive Impairment

IMPORTANCE: Current methods for identifying hospitalized patients at increased risk of delirium require nurse-administered questionnaires with moderate accuracy. OBJECTIVE: To develop and validate a machine learning model that predicts incident delirium risk based on electronic health data available...

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Detalles Bibliográficos
Autores principales: Wong, Andrew, Young, Albert T., Liang, April S., Gonzales, Ralph, Douglas, Vanja C., Hadley, Dexter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Association 2018
Materias:
Original Investigation
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6324291/
https://www.ncbi.nlm.nih.gov/pubmed/30646095
http://dx.doi.org/10.1001/jamanetworkopen.2018.1018

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6324291/
https://www.ncbi.nlm.nih.gov/pubmed/30646095
http://dx.doi.org/10.1001/jamanetworkopen.2018.1018

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