Cargando…
Development and Structure of an Accurate Machine Learning Algorithm to Predict Inpatient Mortality and Hospice Outcomes in the Coronavirus Disease 2019 Era
BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has challenged the accuracy and racial biases present in traditional mortality scores. An accurate prognostic model that can be applied to hospitalized patients irrespective of race or COVID-19 status may benefit patient care. RESEARCH DES...
Autores principales: | Chi, Stephen, Guo, Aixia, Heard, Kevin, Kim, Seunghwan, Foraker, Randi, White, Patrick, Moore, Nathan |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8989608/ https://www.ncbi.nlm.nih.gov/pubmed/35230273 http://dx.doi.org/10.1097/MLR.0000000000001699 |
Ejemplares similares
-
Advanced Care Planning for Hospitalized Patients Following Clinician Notification of Patient Mortality by a Machine Learning Algorithm
por: Chi, Stephen, et al.
Publicado: (2023) -
Predicting mortality among patients with liver cirrhosis in electronic health records with machine learning
por: Guo, Aixia, et al.
Publicado: (2021) -
A Multisite Assessment of Inpatient Safety Event Rates During the Coronavirus Disease 2019 Pandemic
por: Pollock, Benjamin D., et al.
Publicado: (2022) -
The Use of Antibiotics in Hospice and Palliative Care Settings
por: C. Shekhar, Aditya
Publicado: (2022) -
The Efficacy of Hospice Care for Terminally Ill Emergency Patients During the Coronavirus 2019 Pandemic
por: Wang, Qing-Ling, et al.
Publicado: (2022)