Using machine learning techniques for early prediction of tracheal intubation in patients with septic shock: a multi-center study in South Korea

Using machine learning techniques for early prediction of tracheal intubation in patients with septic shock: a multi-center study in South Korea

Background Patients with septic shock frequently require tracheal intubation in the emergency department (ED). However, the criteria for tracheal intubation are subjective, based on physician experience, or require serial evaluations over relatively long intervals to make accurate predictions, which...

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Bibliographic Details
Main Authors: Ji Han Heo, Taegyun Kim, Tae Gun Shin, Gil Joon Suh, Woon Yong Kwon, Hayoung Kim, Heesu Park, Heejun Kim, Sol Han, the Korean Shock Society
Format: Article
Language:English
Published: Korean Society of Critical Care Medicine 2025-05-01
Series:Acute and Critical Care
Subjects:
intubation
machine learning
septic shock
Online Access:http://accjournal.org/upload/pdf/acc-004776.pdf
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http://accjournal.org/upload/pdf/acc-004776.pdf

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