Predicting the Mortality and Readmission of In-Hospital Cardiac Arrest Patients With Electronic Health Records: A Machine Learning Approach

BACKGROUND: In-hospital cardiac arrest (IHCA) is associated with high mortality and health care costs in the recovery phase. Predicting adverse outcome events, including readmission, improves the chance for appropriate interventions and reduces health care costs. However, studies related to the earl...

Descripción completa

Detalles Bibliográficos
Autores principales: Chi, Chien-Yu, Ao, Shuang, Winkler, Adrian, Fu, Kuan-Chun, Xu, Jie, Ho, Yi-Lwun, Huang, Chien-Hua, Soltani, Rohollah
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2021
Materias:
Original Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8477292/
https://www.ncbi.nlm.nih.gov/pubmed/34515639
http://dx.doi.org/10.2196/27798

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8477292/
https://www.ncbi.nlm.nih.gov/pubmed/34515639
http://dx.doi.org/10.2196/27798

Ejemplares similares