A machine learning model for robust prediction of sepsis-induced coagulopathy in critically ill patients with sepsis

A machine learning model for robust prediction of sepsis-induced coagulopathy in critically ill patients with sepsis

IntroductionSepsis-induced coagulopathy (SIC) is a common disease in patients with sepsis. It denotes higher mortality rates and a poorer prognosis in these patients. This study aimed to develop a practical machine learning (ML) model for the prediction of the risk of SIC in critically ill patients...

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Bibliographic Details
Main Authors: Jia Sun, Lixin Zhang, Zhaotang Gong, Hongling Ma, Dan Wu, Rihan Wu, Guleng Siri
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-06-01
Series:Frontiers in Cellular and Infection Microbiology
Subjects:
sepsis
sepsis-induced coagulopathy
risk factor
machine learning
predict
Online Access:https://www.frontiersin.org/articles/10.3389/fcimb.2025.1579558/full
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https://www.frontiersin.org/articles/10.3389/fcimb.2025.1579558/full

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