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

Artificial Intelligence (122) New Methods (911) Artificial Intelligence (1214) Machine Learning (1400) Decision Support for Health Professionals (1145) Clinical Information and Decision Making (1339) Insomnia and Sleep Hygiene (153)

Published on in Vol 2 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/46769, first published .
Self-Supervised Electroencephalogram Representation Learning for Automatic Sleep Staging: Model Development and Evaluation Study

Self-Supervised Electroencephalogram Representation Learning for Automatic Sleep Staging: Model Development and Evaluation Study

Self-Supervised Electroencephalogram Representation Learning for Automatic Sleep Staging: Model Development and Evaluation Study

Authors of this article:

Chaoqi Yang1 Author Orcid Image ;   Cao Xiao2 Author Orcid Image ;   M Brandon Westover3 Author Orcid Image ;   Jimeng Sun1 Author Orcid Image
Article Authors Cited by (3) Tweetations (2) Metrics

Journals

  1. Wu H, Li S, Wu D. Motor Imagery Classification for Asynchronous EEG-Based Brain–Computer Interfaces. IEEE Transactions on Neural Systems and Rehabilitation Engineering 2024;32:527 View
  2. Wang R, Chen Z. Large-scale foundation models and generative AI for BigData neuroscience. Neuroscience Research 2024 View