Use of machine learning-based integration to develop a monocyte differentiation-related signature for improving prognosis in patients with sepsis
Abstract Background Although significant advances have been made in intensive care medicine and antibacterial treatment, sepsis is still a common disease with high mortality. The condition of sepsis patients changes rapidly, and each hour of delay in the administration of appropriate antibiotic trea...
Saved in:
Main Authors: | Jingyuan Ning (Author), Keran Sun (Author), Xuan Wang (Author), Xiaoqing Fan (Author), Keqi Jia (Author), Jinlei Cui (Author), Cuiqing Ma (Author) |
---|---|
Format: | Book |
Published: |
BMC,
2023-03-01T00:00:00Z.
|
Subjects: | |
Online Access: | Connect to this object online. |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
An anoikis-based signature for predicting prognosis in hepatocellular carcinoma with machine learning
by: Zhang Guizhen, et al.
Published: (2023) -
Machine Learning Screening and Validation of PANoptosis-Related Gene Signatures in Sepsis
by: Xu J, et al.
Published: (2024) -
A macrophage related signature for predicting prognosis and drug sensitivity in ovarian cancer based on integrative machine learning
by: Bo Zhao, et al.
Published: (2023) -
Macrophage-Related Gene Signatures for Predicting Prognosis and Immunotherapy of Lung Adenocarcinoma by Machine Learning and Bioinformatics
by: Xiang Y, et al.
Published: (2024) -
Leveraging a disulfidptosis-related signature to predict the prognosis and immunotherapy effectiveness of cutaneous melanoma based on machine learning
by: Yi Zhao, et al.
Published: (2023)