This paper is in the following e-collection/theme issue:

New Methods (964) Machine Learning (1505) Tools, Programs and Algorithms (275) Artificial Intelligence (1430) New and Emerging Methods and Tools in Surgery and Anaesthesiology (42) Postoperative Monitoring and Telemonitoring (128) Mobile tools for surgery and perioperative medicine (85) AI in Neurotechnology (5)

Published on in Vol 23, No 6 (2021): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/25913, first published .
Exploratory Outlier Detection for Acceleromyographic Neuromuscular Monitoring: Machine Learning Approach

Exploratory Outlier Detection for Acceleromyographic Neuromuscular Monitoring: Machine Learning Approach

Exploratory Outlier Detection for Acceleromyographic Neuromuscular Monitoring: Machine Learning Approach

Authors of this article:

Michaël Verdonck1 Author Orcid Image ;   Hugo Carvalho2 Author Orcid Image ;   Johan Berghmans3 Author Orcid Image ;   Patrice Forget4 Author Orcid Image ;   Jan Poelaert2 Author Orcid Image
Article Authors Cited by (7) Tweetations (8) Metrics

Michaël Verdonck   1 * , PhD ;   Hugo Carvalho   2 * , MD, MSc ;   Johan Berghmans   3 , MD, PhD ;   Patrice Forget   4 , MD, PhD ;   Jan Poelaert   2 , MD, PhD

1 Department of Anesthesiology and Perioperative Medicine, Vrije Universiteit Brussel, Jette, Belgium

2 Department of Anesthesiology and Perioperative Medicine, Universitair Ziekenhuis Brussel, Brussel, Belgium

3 Department of Anesthesiology, Ziekenhuis Netwerk Antwerpen, Antwerp, Belgium

4 Department of Anaesthesia, University of Aberdeen, Aberdeen, United Kingdom

*these authors contributed equally

Corresponding Author:

  • Michaël Verdonck, PhD
  • Department of Anesthesiology and Perioperative Medicine
  • Vrije Universiteit Brussel
  • Laarbeeklaan 101
  • Jette, 1050
  • Belgium
  • Phone: 32 474683824
  • Email: michael.verdonck@vub.be