Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Analysis and validation of diagnostic biomarkers and immune cell infiltration characteristics in pediatric sepsis by integrating bioinformatics and machine learning

28 Apr 2023

Abstract excerpt

BACKGROUND: Pediatric sepsis is a complicated condition characterized by life-threatening organ failure resulting from a dysregulated host response to infection in children. It is associated with high rates of morbidity and mortality, and rapid detection and administration of antimicrobials have been emphasized. The objective of this study was to evaluate the diagnostic biomarkers of pediatric sepsis and the...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Immune Response and Inflammation
Share to Inflammation biomarkers and pathways
Share to Sepsis Diagnosis and Treatment

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Source

Identifiers

PMID: 37115484
DOI: 10.1007/s12519-023-00717-7

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 8 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Analysis and validation of diagnostic biomarkers and immune cell infiltration characteristics in pediatric sepsis by integrating bioinformatics and machine learningPMID 37115484Read ↗

Identification of potential transcriptomic markers in developing pediatric sepsis: a weighted gene co-expression network analysis and a case–control validation studySemantic proximity Read ↗

Deciphering the molecular Classification of pediatric sepsis: Integrating WGCNA and Machine learning-based classification with immune signatures for the development of an advanced diagnostic modelSemantic proximity Read ↗

Analysis of signature genes and association with immune cells infiltration in pediatric septic shockSemantic proximity Read ↗

Identification of Immune-Related Key Genes as Potential Diagnostic Biomarkers of Sepsis in ChildrenSemantic proximity Read ↗

Bioinformatics Identification of Immunomodulatory Genes Related to Neonatal Sepsis and Their Incorporation into a Diagnostic ModelSemantic proximity Read ↗

Screening and validation of key genes for pediatric sepsis based on bioinformatics analysisSemantic proximity Read ↗

Diagnostic and Predictive Values of Ferroptosis-Related Genes in Child SepsisSemantic proximity Read ↗

Identification and verification of feature biomarkers associated with immune cells in neonatal sepsisSemantic proximity Read ↗

Identification and validation of potential genes for the diagnosis of sepsis by bioinformatics and 2-sample Mendelian randomization studySemantic proximity Read ↗

Screening of Key Genes of Sepsis and Septic Shock Using Bioinformatics AnalysisSemantic proximity Read ↗

Machine learning driven identification of gene-expression signatures correlated with multiple organ dysfunction trajectories and complex sub-endotypes of pediatric septic shockSemantic proximity Read ↗

Identification of key genes and novel immune infiltration-associated biomarkers of sepsisSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.