A six‑gene support vector machine classifier contributes to the diagnosis of pediatric septic shock
Author:
Affiliation:
1. Department of The Intensive Care Unit, Eastern Hospital, Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital, Chengdu, Sichuan 610101, P.R. China
Publisher
Spandidos Publications
Subject
Cancer Research,Oncology,Genetics,Molecular Biology,Molecular Medicine,Biochemistry
Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Screening and Identification of Neutrophil Extracellular Trap-related Diagnostic Biomarkers for Pediatric Sepsis by Machine Learning;Inflammation;2024-05-25
2. Genetic polymorphisms, biomarkers and signaling pathways associated with septic shock: from diagnosis to therapeutic targets;Burns & Trauma;2024-01-01
3. ADVANCING THE UNDERSTANDING OF CLINICAL SEPSIS USING GENE EXPRESSION–DRIVEN MACHINE LEARNING TO IMPROVE PATIENT OUTCOMES;Shock;2023-09-22
4. Identification and validation of disulfidptosis-associated molecular clusters in non-alcoholic fatty liver disease;Frontiers in Genetics;2023-09-08
5. Transcriptomic marker screening for evaluating the mortality rate of pediatric sepsis based on Henry gas solubility optimization;Alexandria Engineering Journal;2023-04
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