The application of a neural network to predict hypotension and vasopressor requirements non-invasively in obstetric patients having spinal anesthesia for elective cesarean section (C/S)

The application of a neural network to predict hypotension and vasopressor requirements non-invasively in obstetric patients having spinal anesthesia for elective cesarean section (C/S)

Abstract Background Neural networks are increasingly used to assess physiological processes or pathologies, as well as to predict the increased likelihood of an impending medical crisis, such as hypotension. Method We compared the capabilities of a single hidden layer neural network of 12 nodes to t...

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Bibliographic Details
Main Authors: Irwin Gratz, Martin Baruch, Magdy Takla, Julia Seaman, Isabel Allen, Brian McEniry, Edward Deal
Format: Article
Language:English
Published: BMC 2020-05-01
Series:BMC Anesthesiology
Subjects:
Arterial stiffness
Cesarean section
Finger cuff
Hypotension
Neural network
Non-invasive
Online Access:http://link.springer.com/article/10.1186/s12871-020-01015-9

Internet

http://link.springer.com/article/10.1186/s12871-020-01015-9

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