Machine learning for the early prediction of acute respiratory distress syndrome (ARDS) in patients with sepsis in the ICU based on clinical data

Machine learning for the early prediction of acute respiratory distress syndrome (ARDS) in patients with sepsis in the ICU based on clinical data

Background: Acute respiratory distress syndrome (ARDS) is a fatal outcome of severe sepsis. Machine learning models are helpful for accurately predicting ARDS in patients with sepsis at an early stage. Objective: We aim to develop a machine-learning model for predicting ARDS in patients with sepsis...

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Bibliographic Details
Main Authors: Zhenzhen Jiang, Leping Liu, Lin Du, Shanshan Lv, Fang Liang, Yanwei Luo, Chunjiang Wang, Qin Shen
Format: Article
Language:English
Published: Elsevier 2024-03-01
Series:Heliyon
Subjects:
Acute respiratory distress syndrome
ARDS
Machine learning
Algorithm
Sepsis
ICU
Online Access:http://www.sciencedirect.com/science/article/pii/S2405844024041744

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http://www.sciencedirect.com/science/article/pii/S2405844024041744

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