Development and validation of a screening tool for sepsis without laboratory results in the emergency department: a machine learning studyResearch in context

Development and validation of a screening tool for sepsis without laboratory results in the emergency department: a machine learning studyResearch in context

Summary: Background: Sepsis is a significant health burden on a global scale. Timely identification and treatment of sepsis can greatly improve patient outcomes, including survival rates. However, time-consuming laboratory results are often needed for screening sepsis. We aimed to develop a quick s...

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Bibliographic Details
Main Authors: Shan Jiang, Shuai Dai, Yulin Li, Xianlong Zhou, Cheng Jiang, Cong Tian, Yana Yuan, Chengwei Li, Yan Zhao
Format: Article
Language:English
Published: Elsevier 2025-02-01
Series:EClinicalMedicine
Subjects:
Sepsis
Machine learning
Emergency service
Electronic health records
Clinical decision support systems
Online Access:http://www.sciencedirect.com/science/article/pii/S2589537024006278
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