Automated machine learning‐based model predicts postoperative delirium using readily extractable perioperative collected electronic data

OBJECTIVE: Postoperative delirium (POD) is a common postoperative complication that is relevant to poor outcomes. Therefore, it is critical to find effective methods to identify patients with high risk of POD rapidly. Creating a fully automated score based on an automated machine‐learning algorithm...

Descripción completa

Detalles Bibliográficos
Autores principales: Hu, Xiao‐Yi, Liu, He, Zhao, Xue, Sun, Xun, Zhou, Jian, Gao, Xing, Guan, Hui‐Lian, Zhou, Yang, Zhao, Qiu, Han, Yuan, Cao, Jun‐Li
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Original Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8928919/
https://www.ncbi.nlm.nih.gov/pubmed/34792857
http://dx.doi.org/10.1111/cns.13758

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8928919/
https://www.ncbi.nlm.nih.gov/pubmed/34792857
http://dx.doi.org/10.1111/cns.13758

Ejemplares similares