An Explainable Machine-Learning Model for Compensatory Reserve Measurement: Methods for Feature Selection and the Effects of Subject Variability

An Explainable Machine-Learning Model for Compensatory Reserve Measurement: Methods for Feature Selection and the Effects of Subject Variability

Tracking vital signs accurately is critical for triaging a patient and ensuring timely therapeutic intervention. The patient’s status is often clouded by compensatory mechanisms that can mask injury severity. The compensatory reserve measurement (<i>CRM</i>) is a triaging tool derived fr...

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Bibliographic Details
Main Authors: Carlos N. Bedolla, Jose M. Gonzalez, Saul J. Vega, Víctor A. Convertino, Eric J. Snider
Format: Article
Language:English
Published: MDPI AG 2023-05-01
Series:Bioengineering
Subjects:
compensatory mechanisms
machine learning
feature extraction
signal processing
personalized medicine
lower body negative pressure
Online Access:https://www.mdpi.com/2306-5354/10/5/612

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https://www.mdpi.com/2306-5354/10/5/612

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