Cargando…
Machine Learning and Causal Approaches to Predict Readmissions and Its Economic Consequences Among Canadian Patients With Heart Disease: Retrospective Study
BACKGROUND: Unplanned patient readmissions within 30 days of discharge pose a substantial challenge in Canadian health care economics. To address this issue, risk stratification, machine learning, and linear regression paradigms have been proposed as potential predictive solutions. Ensemble machine...
Autores principales: | Rajkumar, Ethan, Nguyen, Kevin, Radic, Sandra, Paa, Jubelle, Geng, Qiyang |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10257109/ https://www.ncbi.nlm.nih.gov/pubmed/37234042 http://dx.doi.org/10.2196/41725 |
Ejemplares similares
-
Road traffic accidents in Ghana: contributing factors and economic consequences
por: Blankson, Paa Kwesi, et al.
Publicado: (2020) -
The Economic and Long-Term Health Consequences of Canadian COVID-19 Lockdowns
por: Bryan, Kevin A., et al.
Publicado: (2021) -
Consequence of causality
por: Mihul, E A
Publicado: (1994) -
A Machine Learning Model for Predicting the Risk of Readmission in Community-Acquired Pneumonia
por: Aldhoayan, Mohammed D, et al.
Publicado: (2022) -
Machine learning based readmission and mortality prediction in heart failure patients
por: Sabouri, Maziar, et al.
Publicado: (2023)