Cargando…
Exploring the Role of Different Cell-Death-Related Genes in Sepsis Diagnosis Using a Machine Learning Algorithm
Sepsis, a disease caused by severe infection, has a high mortality rate. At present, there is a lack of reliable algorithmic models for biomarker mining and diagnostic model construction for sepsis. Programmed cell death (PCD) has been shown to play a vital role in disease occurrence and progression...
Autores principales: | Wang, Xuesong, Wang, Ziyi, Guo, Zhe, Wang, Ziwen, Chen, Feng, Wang, Zhong |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10572834/ https://www.ncbi.nlm.nih.gov/pubmed/37834169 http://dx.doi.org/10.3390/ijms241914720 |
Ejemplares similares
-
Diagnostic and predictive values of pyroptosis-related genes in sepsis
por: Wang, Xuesong, et al.
Publicado: (2023) -
Application Prospect of the SOFA Score and Related Modification Research Progress in Sepsis
por: Wang, Xuesong, et al.
Publicado: (2023) -
A PREDICTION MODEL FOR SEPSIS IN INFECTED PATIENTS: EARLY ASSESSMENT OF SEPSIS ENGAGEMENT
por: Guo, Siying, et al.
Publicado: (2023) -
In silico high-throughput screening system for AKT1 activators with therapeutic applications in sepsis acute lung injury
por: Wang, Ziyi, et al.
Publicado: (2022) -
Hsa_circ_0074158 regulates the endothelial barrier function in sepsis and its potential value as a biomarker
por: Liao, Haiyan, et al.
Publicado: (2022)