Cargando…
Predicting hospitalization of COVID-19 positive patients using clinician-guided machine learning methods
OBJECTIVES: The coronavirus disease 2019 (COVID-19) is a resource-intensive global pandemic. It is important for healthcare systems to identify high-risk COVID-19-positive patients who need timely health care. This study was conducted to predict the hospitalization of older adults who have tested po...
Autores principales: | Song, Wenyu, Zhang, Linying, Liu, Luwei, Sainlaire, Michael, Karvar, Mehran, Kang, Min-Jeoung, Pullman, Avery, Lipsitz, Stuart, Massaro, Anthony, Patil, Namrata, Jasuja, Ravi, Dykes, Patricia C |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9129151/ https://www.ncbi.nlm.nih.gov/pubmed/35595237 http://dx.doi.org/10.1093/jamia/ocac083 |
Ejemplares similares
-
Healthcare Process Modeling to Phenotype Clinician Behaviors for Exploiting the Signal Gain of Clinical Expertise (HPM-ExpertSignals): Development and evaluation of a conceptual framework
por: Rossetti, Sarah Collins, et al.
Publicado: (2021) -
Clinician collaboration to improve clinical decision support: the Clickbusters initiative
por: McCoy, Allison B, et al.
Publicado: (2022) -
The Clinician's Guide to the Machine Learning Galaxy
por: Shen, Lin, et al.
Publicado: (2021) -
Insecure messaging: how clinicians approach potentially problematic messages from patients
por: Lee, Joy L, et al.
Publicado: (2020) -
Assessing the impact of the COVID-19 pandemic on clinician ambulatory electronic health record use
por: Holmgren, A Jay, et al.
Publicado: (2021)