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

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

Books/Policy Documents

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