Estimation of Stroke Volume Variance from Arterial Blood Pressure: Using a 1-D Convolutional Neural Network

Estimation of Stroke Volume Variance from Arterial Blood Pressure: Using a 1-D Convolutional Neural Network

Background: We aimed to create a novel model using a deep learning method to estimate stroke volume variation (SVV), a widely used predictor of fluid responsiveness, from arterial blood pressure waveform (ABPW). Methods: In total, 557 patients and 8,512,564 SVV datasets were collected and were divid...

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Bibliographic Details
Main Authors: Hye-Mee Kwon, Woo-Young Seo, Jae-Man Kim, Woo-Hyun Shim, Sung-Hoon Kim, Gyu-Sam Hwang
Format: Article
Language:English
Published: MDPI AG 2021-07-01
Series:Sensors
Subjects:
stroke volume variance
deep learning
prediction
CNN model
mechanical ventilation
diagnostic
Online Access:https://www.mdpi.com/1424-8220/21/15/5130

Internet

https://www.mdpi.com/1424-8220/21/15/5130

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