Predicting 30-Day Readmission for Stroke Using Machine Learning Algorithms: A Prospective Cohort Study

BACKGROUND: Machine learning algorithms for predicting 30-day stroke readmission are rarely discussed. The aims of this study were to identify significant predictors of 30-day readmission after stroke and to compare prediction accuracy and area under the receiver operating characteristic (AUROC) cur...

Descripción completa

Detalles Bibliográficos
Autores principales: Chen, Yu-Ching, Chung, Jo-Hsuan, Yeh, Yu-Jo, Lou, Shi-Jer, Lin, Hsiu-Fen, Lin, Ching-Huang, Hsien, Hong-Hsi, Hung, Kuo-Wei, Yeh, Shu-Chuan Jennifer, Shi, Hon-Yi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Neurology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9289395/
https://www.ncbi.nlm.nih.gov/pubmed/35860493
http://dx.doi.org/10.3389/fneur.2022.875491

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9289395/
https://www.ncbi.nlm.nih.gov/pubmed/35860493
http://dx.doi.org/10.3389/fneur.2022.875491

Ejemplares similares