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

Decision Support for Health Professionals (1588) Machine Learning (2164) Artificial Intelligence (2242) Safety and Error Prevention in Health (248) Patient Monitoring and Anesthesia Information Management Systems (20)

Published on in Vol 14 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/77830, first published .
Enhancing Anesthetic Depth Assessment via Unsupervised Machine Learning in Processed Electroencephalography Analysis: Novel Methodological Study

Enhancing Anesthetic Depth Assessment via Unsupervised Machine Learning in Processed Electroencephalography Analysis: Novel Methodological Study

Enhancing Anesthetic Depth Assessment via Unsupervised Machine Learning in Processed Electroencephalography Analysis: Novel Methodological Study

Authors of this article:

Po-Yu Huang1 Author Orcid Image ;   Wei-Lun Hong2 Author Orcid Image ;   Hui-Zen Hee3 Author Orcid Image ;   Wen-Kuei Chang1 Author Orcid Image ;   Ching-Hung Lee2, 4 Author Orcid Image ;   Chien-Kun Ting1, 5 Author Orcid Image
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