Funding Information: This research was funded by the Flanders Innovation and Entrepreneurship Fund, the Willy Gepts Fund for Scientific Research, and the Society for Anesthesia and Resuscitation of Belgium (SARB). Publisher Copyright: © Michaël Verdonck, Hugo Carvalho, Johan Berghmans, Patrice Forget, Jan Poelaert. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 06.06.2021. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly ci...
International audienceEvery year, millions of patients regain consciousness during surgery and can p...
The goal of this study was to identify features in mouse electrocorticogram recordings that indicate...
Machine learning (ML) is revolutionizing anesthesiology research. Unlike classical research methods ...
BackgroundBecause of their kinetic nature, artifactual recordings of acceleromyography-based neuromu...
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The credibility of threshold-based alarms in anesthesia monitors is low and most of the warnings the...
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Anesthesia providers are responsible for administering neuromuscular blocking agents, monitoring the...
Outlier detection is an important problem with diverse practical applications. In medical imaging, t...
BACKGROUND: Residual neuromuscular block is defined as a mechanomyography (MMG) or electromyography ...
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Abstract Neuromuscular block monitoring is recommended by international guidelines to improve myorel...
This project considers the need to use machine learning for supporting anaesthesiologists to predict...
International audienceEvery year, millions of patients regain consciousness during surgery and can p...
The goal of this study was to identify features in mouse electrocorticogram recordings that indicate...
Machine learning (ML) is revolutionizing anesthesiology research. Unlike classical research methods ...
BackgroundBecause of their kinetic nature, artifactual recordings of acceleromyography-based neuromu...
Background: Quantitative neuromuscular monitoring is the gold standard to detect postoperative resid...
The credibility of threshold-based alarms in anesthesia monitors is low and most of the warnings the...
The occurrence of postoperative residual neuromuscular blockade continues to affect a considerable p...
Quantitative neuromuscular block (NMB) assessment is an internationally recognised necessity in anes...
Anesthesia providers are responsible for administering neuromuscular blocking agents, monitoring the...
Anesthesia providers are responsible for administering neuromuscular blocking agents, monitoring the...
Outlier detection is an important problem with diverse practical applications. In medical imaging, t...
BACKGROUND: Residual neuromuscular block is defined as a mechanomyography (MMG) or electromyography ...
Winkler-Schwartz et al have set out to determine if some combination of machine learning algorithms ...
Abstract Neuromuscular block monitoring is recommended by international guidelines to improve myorel...
This project considers the need to use machine learning for supporting anaesthesiologists to predict...
International audienceEvery year, millions of patients regain consciousness during surgery and can p...
The goal of this study was to identify features in mouse electrocorticogram recordings that indicate...
Machine learning (ML) is revolutionizing anesthesiology research. Unlike classical research methods ...