Machine Learning Identifies Complicated Sepsis Course and Subsequent Mortality Based on 20 Genes in Peripheral Blood Immune Cells at 24 H Post-ICU Admission

Machine Learning Identifies Complicated Sepsis Course and Subsequent Mortality Based on 20 Genes in Peripheral Blood Immune Cells at 24 H Post-ICU Admission

A complicated clinical course for critically ill patients admitted to the intensive care unit (ICU) usually includes multiorgan dysfunction and subsequent death. Owing to the heterogeneity, complexity, and unpredictability of the disease progression, ICU patient care is challenging. Identifying the...

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Bibliographic Details
Main Authors: Shayantan Banerjee, Akram Mohammed, Hector R. Wong, Nades Palaniyar, Rishikesan Kamaleswaran
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-02-01
Series:Frontiers in Immunology
Subjects:
sepsis
complicated course
critical care
machine learning
transcriptomics
biomarkers
Online Access:https://www.frontiersin.org/articles/10.3389/fimmu.2021.592303/full

Internet

https://www.frontiersin.org/articles/10.3389/fimmu.2021.592303/full

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