Analysis and validation of diagnostic biomarkers and immune cell infiltration characteristics in pediatric sepsis by integrating bioinformatics and machine learning.
Wen-Yuan ZhangZhong-Hua ChenXiao-Xia AnHui LiHua-Lin ZhangShui-Jing WuYu-Qian GuoKai ZhangCong-Li ZengXiang-Ming FangPublished in: World journal of pediatrics : WJP (2023)
The candidate hub genes (CD177, CYSTM1, and MMP8) were identified, and the nomogram was constructed for pediatric sepsis diagnosis. Our study could provide potential peripheral blood diagnostic candidate genes for pediatric sepsis patients.
Keyphrases
- intensive care unit
- acute kidney injury
- peripheral blood
- septic shock
- machine learning
- end stage renal disease
- ejection fraction
- chronic kidney disease
- newly diagnosed
- wastewater treatment
- gene expression
- artificial intelligence
- young adults
- dna methylation
- lymph node metastasis
- risk assessment
- transcription factor
- climate change