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

New Methods (1140) Machine Learning (2095) Tools, Programs and Algorithms (384) Artificial Intelligence (2162) New and Emerging Methods and Tools in Surgery and Anesthesiology (54) Postoperative Monitoring and Telemonitoring (195) Mobile tools for surgery and perioperative medicine (101) AI in Neurotechnology (9)

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 (8) Tweetations (6) Metrics

Journals

  1. Park D, Kim I. Application of Machine Learning in the Field of Intraoperative Neurophysiological Monitoring: A Narrative Review. Applied Sciences 2022;12(15):7943 View
  2. Carvalho H, Verdonck M, Brull S, Fuchs-Buder T, Forget P, Flamée P, Poelaert J. A survey on the availability, usage and perception of neuromuscular monitors in Europe. Journal of Clinical Monitoring and Computing 2023;37(2):549 View
  3. Vanhonacker D, Verdonck M, Nogueira Carvalho H. Impact of Closed-Loop Technology, Machine Learning, and Artificial Intelligence on Patient Safety and the Future of Anesthesia. Current Anesthesiology Reports 2022;12(4):451 View
  4. Wilson Jr J, Kumbhare D, Kandregula S, Oderhowho A, Guthikonda B, Hoang S. Proposed applications of machine learning to intraoperative neuromonitoring during spine surgeries. Neuroscience Informatics 2023;3(4):100143 View
  5. Gheysen F, Rex S. Artificial intelligence in anesthesiology. Acta Anaesthesiologica Belgica 2023;74(3):185 View
  6. Omer A, Ali T. Dealing with the Outlier Problem in Multivariate Linear Regression Analysis Using the Hampel Filter. Kurdistan Journal of Applied Research 2025;10(1):1 View

Books/Policy Documents

  1. Bignami E, Bellini V, Carnà E. The High-risk Surgical Patient. View

Conference Proceedings

  1. Weichao W, Li X, Haisheng H. 2023 International Conference on Applied Intelligence and Sustainable Computing (ICAISC). Graphic Model Features of Distribution Network Electrical Engineering Based on Machine Learning Algorithm View