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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...
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 |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
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Materias: | |
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 |
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