Random forest differentiation of Escherichia coli in elderly sepsis using biomarkers and infectious sites

Random forest differentiation of Escherichia coli in elderly sepsis using biomarkers and infectious sites

Abstract This study addresses the challenge of accurately diagnosing sepsis subtypes in elderly patients, particularly distinguishing between Escherichia coli (E. coli) and non-E. coli infections. Utilizing machine learning, we conducted a retrospective analysis of 119 elderly sepsis patients, emplo...

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Bibliographic Details
Main Authors: Bu-Ren Li, Ying Zhuo, Ying-Ying Jiang, Shi-Yan Zhang
Format: Article
Language:English
Published: Nature Portfolio 2024-06-01
Series:Scientific Reports
Subjects:
Sepsis
Elderly
Machine learning
Random forest
Escherichia coli
Diagnostic accuracy
Online Access:https://doi.org/10.1038/s41598-024-63944-6

Internet

https://doi.org/10.1038/s41598-024-63944-6

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