Loading…
AI-Enabled Advanced Development for Assessing Low Circulating Blood Volume for Emergency Medical Care: Comparison of Compensatory Reserve Machine-Learning Algorithms
The application of artificial intelligence (AI) has provided new capabilities to develop advanced medical monitoring sensors for detection of clinical conditions of low circulating blood volume such as hemorrhage. The purpose of this study was to compare for the first time the discriminative ability...
Main Authors: | Convertino, Victor A., Techentin, Robert W., Poole, Ruth J., Dacy, Ashley C., Carlson, Ashli N., Cardin, Sylvain, Haider, Clifton R., Holmes III, David R., Wiggins, Chad C., Joyner, Michael J., Curry, Timothy B., Inan, Omer T. |
---|---|
Format: | Online Article Text |
Language: | English |
Published: |
MDPI
2022
|
Subjects: | |
Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9003258/ https://www.ncbi.nlm.nih.gov/pubmed/35408255 http://dx.doi.org/10.3390/s22072642 |
Similar Items
-
Wearable Sensors Incorporating Compensatory Reserve Measurement for Advancing Physiological Monitoring in Critically Injured Trauma Patients
by: Convertino, Victor A., et al.
Published: (2020) -
Wearable Sensors and Machine Learning for Hypovolemia Problems in Occupational, Military and Sports Medicine: Physiological Basis, Hardware and Algorithms
by: Kimball, Jacob P., et al.
Published: (2022) -
Variability in integration of mechanisms associated with high tolerance to progressive reductions in central blood volume: the compensatory reserve
by: Carter, Robert, et al.
Published: (2016) -
Bridging the gap between military prolonged field care monitoring and exploration spaceflight: the compensatory reserve
by: Schlotman, Taylor E., et al.
Published: (2019) -
An Explainable Machine-Learning Model for Compensatory Reserve Measurement: Methods for Feature Selection and the Effects of Subject Variability
by: Bedolla, Carlos N., et al.
Published: (2023)