Supervised Machine Learning Applied to Automate Flash and Prolonged Capillary Refill Detection by Pulse Oximetry

Supervised Machine Learning Applied to Automate Flash and Prolonged Capillary Refill Detection by Pulse Oximetry

ObjectiveDevelop an automated approach to detect flash (<1.0 s) or prolonged (>2.0 s) capillary refill time (CRT) that correlates with clinician judgment by applying several supervised machine learning (ML) techniques to pulse oximeter plethysmography data.Materials and MethodsData was...

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Bibliographic Details
Main Authors: Ryan Brandon Hunter, Shen Jiang, Akira Nishisaki, Amanda J. Nickel, Natalie Napolitano, Koichiro Shinozaki, Timmy Li, Kota Saeki, Lance B. Becker, Vinay M. Nadkarni, Aaron J. Masino
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-10-01
Series:Frontiers in Physiology
Subjects:
perfusion
oximetry
supervised machine learning
intensive care units
pediatrics
gradient boosting
Online Access:https://www.frontiersin.org/article/10.3389/fphys.2020.564589/full

Internet

https://www.frontiersin.org/article/10.3389/fphys.2020.564589/full

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