Subphenotyping heterogeneous patients with chronic critical illness to guide individualised fluid balance treatment using machine learning: a retrospective cohort studyResearch in context

Subphenotyping heterogeneous patients with chronic critical illness to guide individualised fluid balance treatment using machine learning: a retrospective cohort studyResearch in context

Summary: Background: The great heterogeneity of patients with chronic critical illness (CCI) leads to difficulty for intensive care unit (ICU) management. Identifying subphenotypes could assist in individualized care, which has not yet been explored. In this study, we aim to identify the subphenoty...

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Bibliographic Details
Main Authors: Peizhao Liu, Sicheng Li, Tao Zheng, Jie Wu, Yong Fan, Xiaoli Liu, Wenbin Gong, Haohao Xie, Juanhan Liu, Yangguang Li, Haiyang Jiang, Fan Zhao, Jinpeng Zhang, Lei Wu, Huajian Ren, Zhiwu Hong, Jun Chen, Guosheng Gu, Gefei Wang, Zhengbo Zhang, Xiuwen Wu, Yun Zhao, Jianan Ren
Format: Article
Language:English
Published: Elsevier 2023-05-01
Series:EClinicalMedicine
Subjects:
Chronic critical illness
Unsupervised learning
Subclass
Critical care
Heterogeneous treatment effect
Online Access:http://www.sciencedirect.com/science/article/pii/S2589537023001475

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