Detection of a Stroke Volume Decrease by Machine-Learning Algorithms Based on Thoracic Bioimpedance in Experimental Hypovolaemia

Detection of a Stroke Volume Decrease by Machine-Learning Algorithms Based on Thoracic Bioimpedance in Experimental Hypovolaemia

Compensated shock and hypovolaemia are frequent conditions that remain clinically undetected and can quickly cause deterioration of perioperative and critically ill patients. Automated, accurate and non-invasive detection methods are needed to avoid such critical situations. In this experimental stu...

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Bibliographic Details
Main Authors: Matthias Stetzuhn, Timo Tigges, Alexandru Gabriel Pielmus, Claudia Spies, Charlotte Middel, Michael Klum, Sebastian Zaunseder, Reinhold Orglmeister, Aarne Feldheiser
Format: Article
Language:English
Published: MDPI AG 2022-07-01
Series:Sensors
Subjects:
compensated shock
electrical cardiometry
hypovolaemia
lower body negative pressure chamber
machine learning
prediction model
Online Access:https://www.mdpi.com/1424-8220/22/14/5066

Internet

https://www.mdpi.com/1424-8220/22/14/5066

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