A diagnostic model for sepsis-induced acute lung injury using a consensus machine learning approach and its therapeutic implications

A diagnostic model for sepsis-induced acute lung injury using a consensus machine learning approach and its therapeutic implications

Abstract Background A significant proportion of septic patients with acute lung injury (ALI) are recognized late due to the absence of an efficient diagnostic test, leading to the postponed treatments and consequently higher mortality. Identifying diagnostic biomarkers may improve screening to ident...

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Bibliographic Details
Main Authors: Yongxin Zheng, Jinping Wang, Zhaoyi Ling, Jiamei Zhang, Yuan Zeng, Ke Wang, Yu Zhang, Lingbo Nong, Ling Sang, Yonghao Xu, Xiaoqing Liu, Yimin Li, Yongbo Huang
Format: Article
Language:English
Published: BMC 2023-09-01
Series:Journal of Translational Medicine
Subjects:
Sepsis
Acute lung injury
Acute respiratory distress syndrome
Machine learning
Transcriptome
Online Access:https://doi.org/10.1186/s12967-023-04499-4

Internet

https://doi.org/10.1186/s12967-023-04499-4

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