Validation of a convolutional neural network that reliably identifies electromyographic compound motor action potentials following train-of-four stimulation. Comment on Br J Anaesth Open 2023; 8: 100236-Reference-Cited by-同舟云学术

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Validation of a convolutional neural network that reliably identifies electromyographic compound motor action potentials following train-of-four stimulation. Comment on Br J Anaesth Open 2023; 8: 100236

Published:2024-03 Issue: Volume:9 Page:100264
ISSN:2772-6096
Container-title:BJA Open
language:en
Short-container-title:BJA Open

Author:

Silliman Willis,Wedemeyer Zain,Jelacic Srdjan,Bowdle Andrew^ORCID,Michaelsen Kelly E.^ORCID

Publisher

Elsevier BV

Reference9 articles.

1. Validation of a convolutional neural network that reliably identifies electromyographic compound motor action potentials following train-of-four stimulation: an algorithm development experimental study;Epstein;BJA Open,2023

2. Train-of-four monitoring with the twitchview monitor electctromyograph compared to the GE NMT electromyograph and manual palpation;Bussey;J Clin Monit Comput,2021

3. Comparison of train-of-four count by anesthesia providers versus TOF-Watch® SX: a prospective cohort study;Bhananker;Can J Anesth Can Anesth,2015

4. Counting train-of-four twitch response: comparison of palpation to mechanomyography, acceleromyography, and electromyography;Bowdle;Br J Anaesth,2020

5. Neocognitron: a neural network model for a mechanism of visual pattern recognition;Fukushima;IEEE Trans Syst Man Cybern,1983

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